From 54a9a80e830ba9814b39de4076ff6c2b71428104 Mon Sep 17 00:00:00 2001 From: Brian Delhaisse Date: Thu, 13 Jun 2019 17:13:46 +0200 Subject: [PATCH] add kilobot (unfinished) + few minor corrections --- pyrobolearn/actorcritics/nn_actorcritic.py | 14 +- pyrobolearn/dynamics/nn_dynamic.py | 15 +- pyrobolearn/optimizers/torch_optimizer.py | 4 +- pyrobolearn/robots/__init__.py | 1 + pyrobolearn/robots/flappy.py | 2 +- pyrobolearn/robots/kilobot.py | 108 + pyrobolearn/robots/urdfs/kilobot/LICENSE | 8 + pyrobolearn/robots/urdfs/kilobot/kilobot.urdf | 195 ++ pyrobolearn/simulators/dart.py | 5 +- pyrobolearn/simulators/raisim.py | 2422 +++++++++++++++++ pyrobolearn/simulators/simulator.py | 2 +- pyrobolearn/values/nn_value.py | 42 +- 12 files changed, 2775 insertions(+), 43 deletions(-) create mode 100644 pyrobolearn/robots/kilobot.py create mode 100644 pyrobolearn/robots/urdfs/kilobot/LICENSE create mode 100644 pyrobolearn/robots/urdfs/kilobot/kilobot.urdf create mode 100644 pyrobolearn/simulators/raisim.py diff --git a/pyrobolearn/actorcritics/nn_actorcritic.py b/pyrobolearn/actorcritics/nn_actorcritic.py index 61c6f4f..4e1d0c9 100644 --- a/pyrobolearn/actorcritics/nn_actorcritic.py +++ b/pyrobolearn/actorcritics/nn_actorcritic.py @@ -29,7 +29,7 @@ class MLPActorCritic(ActorCritic): r"""Multi-Layer Perceptron Actor Critic """ - def __init__(self, states, actions, hidden_units=(), activation_fct='linear', last_activation_fct=None, + def __init__(self, states, actions, hidden_units=(), activation='linear', last_activation=None, dropout_prob=None, rate=1, preprocessors=None, postprocessors=None): """Initialize MLP policy. @@ -39,9 +39,9 @@ class MLPActorCritic(ActorCritic): actions (Action): 1D-actions outputted by the policy and will be applied in the simulator (the output dimensions will be inferred from the actions) hidden_units (list/tuple of int): number of hidden units in the corresponding layer - activation_fct (None, str, or list/tuple of str/None): activation function to be applied after each layer. + activation (None, str, or list/tuple of str/None): activation function to be applied after each layer. If list/tuple, then it has to match the - last_activation_fct (None or str): last activation function to be applied. If not specified, it will check + last_activation (None or str): last activation function to be applied. If not specified, it will check if it is in the list/tuple of activation functions provided for the previous argument. dropout_prob (None, float, or list/tuple of float/None): dropout probability. @@ -51,11 +51,11 @@ class MLPActorCritic(ActorCritic): preprocessors (Processor, list of Processor, None): pre-processors to be applied to the given input postprocessors (Processor, list of Processor, None): post-processors to be applied to the policy's output """ - policy = MLPPolicy(states, actions, hidden_units=hidden_units, activation=activation_fct, - last_activation=last_activation_fct, dropout=dropout_prob, rate=rate, + policy = MLPPolicy(states, actions, hidden_units=hidden_units, activation=activation, + last_activation=last_activation, dropout=dropout_prob, rate=rate, preprocessors=preprocessors, postprocessors=postprocessors) - value = MLPValue(states, hidden_units=hidden_units, activation_fct=activation_fct, - last_activation_fct=last_activation_fct, dropout_prob=dropout_prob, + value = MLPValue(states, hidden_units=hidden_units, activation=activation, + last_activation=last_activation, dropout=dropout_prob, preprocessors=preprocessors) super(MLPActorCritic, self).__init__(policy, value) diff --git a/pyrobolearn/dynamics/nn_dynamic.py b/pyrobolearn/dynamics/nn_dynamic.py index 9ea30e3..b9d5df5 100644 --- a/pyrobolearn/dynamics/nn_dynamic.py +++ b/pyrobolearn/dynamics/nn_dynamic.py @@ -59,9 +59,8 @@ class MLPDynamicModel(NNDynamicModel): """ - def __init__(self, state, action, next_state=None, hidden_units=(), activation_fct='Linear', - last_activation_fct=None, dropout_prob=None, distributions=None, preprocessors=None, - postprocessors=None): + def __init__(self, state, action, next_state=None, hidden_units=(), activation='linear', last_activation=None, + dropout=None, distributions=None, preprocessors=None, postprocessors=None): """ Initialize the multi-layer perceptron model. @@ -70,9 +69,9 @@ class MLPDynamicModel(NNDynamicModel): action (Action): action inputs. next_state (State, None): state outputs. If None, it will take the state inputs as the outputs. hidden_units (tuple, list of int): number of hidden units in each layer - activation_fct (str): activation function to apply on each layer - last_activation_fct (str, None): activation function to apply on the last layer - dropout_prob (None, float): dropout probability + activation (str): activation function to apply on each layer + last_activation (str, None): activation function to apply on the last layer + dropout (None, float): dropout probability distributions (torch.distributions.Distribution): distribution to use to sample the next state. If None, it will be deterministic. preprocessors (Processor, list of Processor, None): pre-processors to be applied to the given input @@ -81,8 +80,8 @@ class MLPDynamicModel(NNDynamicModel): if next_state is None: next_state = state model = MLPApproximator(inputs=[state, action], outputs=next_state, hidden_units=hidden_units, - activation=activation_fct, last_activation=last_activation_fct, - dropout=dropout_prob) + activation=activation, last_activation=last_activation, + dropout=dropout) super(MLPDynamicModel, self).__init__(state, action, model=model, next_state=next_state, distributions=distributions, preprocessors=preprocessors, postprocessors=postprocessors) diff --git a/pyrobolearn/optimizers/torch_optimizer.py b/pyrobolearn/optimizers/torch_optimizer.py index 8687ed1..714ef64 100644 --- a/pyrobolearn/optimizers/torch_optimizer.py +++ b/pyrobolearn/optimizers/torch_optimizer.py @@ -70,7 +70,7 @@ class Adam(Optimizer): # optimize self.optimizer.zero_grad() - loss.backward() + loss.backward(retain_graph=True) if self.max_grad_norm is not None: nn.utils.clip_grad_norm_(params, self.max_grad_norm) self.optimizer.step() @@ -99,7 +99,7 @@ class Adadelta(Optimizer): # optimize self.optimizer.zero_grad() - loss.backward() + loss.backward(retain_graph=True) if self.max_grad_norm is not None: nn.utils.clip_grad_norm_(params, self.max_grad_norm) self.optimizer.step() diff --git a/pyrobolearn/robots/__init__.py b/pyrobolearn/robots/__init__.py index ab80194..77cf1c4 100644 --- a/pyrobolearn/robots/__init__.py +++ b/pyrobolearn/robots/__init__.py @@ -97,6 +97,7 @@ from .centauro import Centauro # UAV from .quadcopter import Quadcopter # from .techpod import Techpod +from .flappy import Flappy # UUV # from .ecaa9 import ECAA9 diff --git a/pyrobolearn/robots/flappy.py b/pyrobolearn/robots/flappy.py index 1e06d18..8d55547 100644 --- a/pyrobolearn/robots/flappy.py +++ b/pyrobolearn/robots/flappy.py @@ -306,7 +306,7 @@ class Flappy(FlappingWingUAV): described in the paper and code [2,3]. The gravity is carried out by pybullet. References: - [1] "Design Optimization and System Integration of Robotic Hummingbird", 2017, Zhang et al. + [1] "Design Optimization and System Integration of Robotic Hummingbird", Zhang et al., 2017 [2] "Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals", Fei et al., 2019 [3] https://github.com/purdue-biorobotics/flappy diff --git a/pyrobolearn/robots/kilobot.py b/pyrobolearn/robots/kilobot.py new file mode 100644 index 0000000..a0edbe5 --- /dev/null +++ b/pyrobolearn/robots/kilobot.py @@ -0,0 +1,108 @@ +#!/usr/bin/env python +"""Provide the Kilobot robotic platform. +""" + +# TODO: finish URDF: fix mass, inertia, dimensions, linear joint (spring mass) +# TODO: implement LRA vibration motor + +import os +import numpy as np + +from pyrobolearn.robots.robot import Robot + +__author__ = "Brian Delhaisse" +__copyright__ = "Copyright 2018, PyRoboLearn" +__license__ = "MIT" +__version__ = "1.0.0" +__maintainer__ = "Brian Delhaisse" +__email__ = "briandelhaisse@gmail.com" +__status__ = "Development" + + +class Kilobot(Robot): + r"""Kilobot robot + + The Kilobot robot [1,2,3,4] is a small robot (diameter=33mm, height=34mm) mostly used in swarm robotics. + It notably uses 2 coin shaped vibration motors [5] allowing the robot to move in a differential drive manner using + the slip-stick principle. + + There are two types of vibration motors: + - eccentric rotating mass vibration motor (ERM) [5.1] + - linear resonant actuator (LRA) [5.2] + + References: + [1] "Kilobot: a Low Cost Scalable Robot System for Collective Behaviors", Rubenstein et al., 2012 + [2] "Programmable self-assembly in a thousand-robot swarm", Rubenstein et al., 2014 + [3] Harvard's Self-Organizing Systems Research Group: https://ssr.seas.harvard.edu/kilobots + [4] K-Team Corporation: https://www.k-team.com/mobile-robotics-products/kilobot + [5] Precision Micro drives: https://www.precisionmicrodrives.com/ + - ERM: https://www.precisionmicrodrives.com/vibration-motors/ + - LRA: https://www.precisionmicrodrives.com/vibration-motors/linear-resonant-actuators-lras/ + """ + + def __init__(self, + simulator, + position=(0, 0, 0), + orientation=(0, 0, 0, 1), + fixed_base=False, + scale=1., + urdf=os.path.dirname(__file__) + '/urdfs/kilobot/kilobot.urdf'): # TODO: finish URDF + # check parameters + if position is None: + position = (0., 0., 0) + if len(position) == 2: # assume x, y are given + position = tuple(position) + (0.0,) + if orientation is None: + orientation = (0, 0, 0, 1) + if fixed_base is None: + fixed_base = False + + super(Kilobot, self).__init__(simulator, urdf, position, orientation, fixed_base, scale) + self.name = 'kilobot' + + # 2 coin shaped vibration motors with 255 different power levels + self.motors = [] + + def drive(self, values): + """ + Drive the kilobot in a differential drive manner using the slip-stick principle. + + Args: + values (float, int, np.array): 255 different power levels [0,255] for each motor. + """ + if isinstance(values, (int, float)): + values = np.ones(len(self.motors)) * values + pass + + +# Test +if __name__ == "__main__": + from itertools import count + from pyrobolearn.simulators import Bullet + from pyrobolearn.worlds import BasicWorld + + # Create simulator + sim = Bullet() + + # create world + world = BasicWorld(sim) + + # create robot + robots = [] + for _ in range(30): + x, y = np.random.uniform(low=-1, high=1, size=2) + robot = world.load_robot(Kilobot, position=(x, y, 0)) + robots.append(robot) + + # print information about the robot + robots[0].print_info() + + # Position control using sliders + # robots[0].add_joint_slider() + + # run simulator + for _ in count(): + # robots[0].update_joint_slider() + for robot in robots: + robot.drive(5) + world.step(sleep_dt=1./240) diff --git a/pyrobolearn/robots/urdfs/kilobot/LICENSE b/pyrobolearn/robots/urdfs/kilobot/LICENSE new file mode 100644 index 0000000..1db7ad1 --- /dev/null +++ b/pyrobolearn/robots/urdfs/kilobot/LICENSE @@ -0,0 +1,8 @@ +Copyright 2019, Brian Delhaisse + +Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + diff --git a/pyrobolearn/robots/urdfs/kilobot/kilobot.urdf b/pyrobolearn/robots/urdfs/kilobot/kilobot.urdf new file mode 100644 index 0000000..b1300da --- /dev/null +++ b/pyrobolearn/robots/urdfs/kilobot/kilobot.urdf @@ -0,0 +1,195 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/pyrobolearn/simulators/dart.py b/pyrobolearn/simulators/dart.py index e06625a..7c4bc92 100644 --- a/pyrobolearn/simulators/dart.py +++ b/pyrobolearn/simulators/dart.py @@ -22,10 +22,11 @@ Dependencies in PRL: Dependencies in PRL: None References: - [1] Dynamic Animation and Robotics Toolkit (DART): + [1] DART: Dynamic Animation and Robotics Toolkit + - paper: http://joss.theoj.org/papers/10.21105/joss.00500 - webpage: https://dartsim.github.io/ - github: https://github.com/dartsim/dart/ - [2] PyDART: + [2] PyDART - source code: https://pydart2.readthedocs.io/en/latest/ - documentation: https://pydart2.readthedocs.io/en/latest/ [3] PEP8: https://www.python.org/dev/peps/pep-0008/ diff --git a/pyrobolearn/simulators/raisim.py b/pyrobolearn/simulators/raisim.py new file mode 100644 index 0000000..4ff7d3f --- /dev/null +++ b/pyrobolearn/simulators/raisim.py @@ -0,0 +1,2422 @@ +#!/usr/bin/env python +"""Define the RaiSim Simulator API. + +Warnings: Currently, the RaiSim simulator is closed-source and is only available for researchers at RSL and ETH Zurich. + +This is the main interface that communicates with the RaiSim simulator [1, 2]. By defining this interface, it allows to +decouple the PyRoboLearn framework from the simulator. It also converts some data types to the ones required by +RaiSim. + +The signature of each method defined here are inspired by [1,2] but in accordance with the PEP8 style guide [3]. +Parts of the documentation for the methods have been copied-pasted from [2] for completeness purposes. + +Dependencies in PRL: +* `pyrobolearn.simulators.simulator.Simulator` + +References: + [1] "Per-Contact Iteration Method for Solving Contact Dynamics", Hwangbo et al., 2018 + [2] RaiSim: https://leggedrobotics.github.io/SimBenchmark/about/sims.html + [3] PEP8: https://www.python.org/dev/peps/pep-0008/ +""" + +# TODO: +# 1. wait for ETH to release the simulator (not sure if they will ever do it...) +# 2. check if a Python wrapper is provided, if not, will have to implement it + +# import PRL simulator +from pyrobolearn.simulators.simulator import Simulator + +__author__ = "Brian Delhaisse" +__copyright__ = "Copyright 2018, PyRoboLearn" +__credits__ = ["Brian Delhaisse"] +__license__ = "MIT" +__version__ = "1.0.0" +__maintainer__ = "Brian Delhaisse" +__email__ = "briandelhaisse@gmail.com" +__status__ = "Development" + + +class Raisim(Simulator): + r"""RaiSim + + This is a wrapper around the RaiSim simulator [1,2]. Currently, the simulator is closed-source and is only + available for researchers at RSL and ETH Zurich. + + Examples: + sim = Raisim() + + References: + [1] "Per-Contact Iteration Method for Solving Contact Dynamics", Hwangbo et al., 2018 + [2] RaiSim: https://leggedrobotics.github.io/SimBenchmark/about/sims.html + """ + + def __init__(self, render=True, **kwargs): + super(Raisim, self).__init__(render, **kwargs) + raise NotImplementedError("The RaiSim simulator is not currently available as it has not been released for " + "the moment") + + ############## + # Properties # + ############## + + @property + def version(self): + """Return the version of the simulator.""" + return 0 + + @property + def gravity(self): + """Return the gravity in the simulator.""" + return self.get_gravity() + + @gravity.setter + def gravity(self, gravity): + """Set the gravity in the simulator.""" + self.set_gravity(gravity) + + @property + def camera(self): + """Return the camera (yaw, pitch, distance, target_position) or None.""" + return self._camera + + ############# + # Operators # + ############# + + def __str__(self): + """Return a readable string about the class.""" + return self.__class__.__name__ + + def __del__(self): + """Close/Delete the simulator.""" + self.close() + + def __copy__(self): + """Return a shallow copy of the simulator. This can be overridden in the child class.""" + return self.__class__(render=self._render, **self.kwargs) + + def __deepcopy__(self, memo={}): + """Return a deep copy of the simulator. This can be overridden in the child class. + + Args: + memo (dict): memo dictionary of objects already copied during the current copying pass. + """ + # if the object has already been copied return the reference to the copied object + if self in memo: + return memo[self] + + # create a new copy of the simulator + sim = self.__class__(render=self._render, **self.kwargs) + + memo[self] = sim + return sim + + ########### + # Methods # + ########### + + # Simulators + + def reset(self, *args, **kwargs): + """Reset the simulator.""" + pass + + def close(self): + """Close the simulator.""" + pass + + def seed(self, seed=None): + """Set the given seed in the simulator.""" + pass + + def step(self, sleep_time=0): + """Perform a step in the simulator, and sleep the specified time. + + Args: + sleep_time (float): time to sleep after performing one step in the simulation. + """ + pass + + def is_rendering(self): + """Return True if the simulator is in the render mode.""" + return self._render + + def reset_scene_camera(self, camera=None): + """ + Reinitialize/Reset the scene view camera to the previous one. + + Args: + camera (object): scene view camera. This is let to the user to decide what to do. + """ + pass + + def render(self, enable=True): + """Render the simulation. + + Args: + enable (bool): If True, it will render the simulator by enabling the GUI. + """ + self._render = enable + + def hide(self): + """Hide the GUI.""" + self.render(False) + + def set_time_step(self, time_step): + """Set the time step in the simulator. + + Args: + time_step (float): Each time you call 'step' the time step will proceed with 'time_step'. + """ + pass + + def set_real_time(self, enable=True): + """Enable real time in the simulator. + + Args: + enable (bool): If True, it will enable the real-time simulation. If False, it will disable it. + """ + pass + + def pause(self): + """Pause the simulator if in real-time.""" + pass + + def unpause(self): + """Unpause the simulator if in real-time.""" + pass + + def get_physics_properties(self): + """Get the physics engine parameters.""" + pass + + def set_physics_properties(self, *args, **kwargs): + """Set the physics engine parameters.""" + pass + + def start_logging(self, *args, **kwargs): + """Start the logging.""" + pass + + def stop_logging(self, logger_id): + """Stop the logging.""" + pass + + def get_gravity(self): + """Return the gravity set in the simulator.""" + pass + + def set_gravity(self, gravity=(0, 0, -9.81)): + """Set the gravity in the simulator with the given acceleration. + + Args: + gravity (list, tuple of 3 floats): acceleration in the x, y, z directions. + """ + pass + + def save(self, filename=None, *args, **kwargs): + """Save the state of the simulator. + + Args: + filename (None, str): path to file to store the state of the simulator. If None, it will save it in + memory instead of the disk. + + Returns: + int: unique state id. This id can be used to load the state. + """ + pass + + def load(self, state, *args, **kwargs): + """Load / Restore the simulator to a previous state. + + Args: + state (int, str): unique state id, or path to the file containing the state. + """ + pass + + def load_plugin(self, plugin_path, name, *args, **kwargs): + """Load a certain plugin in the simulator. + + Args: + plugin_path (str): path, location on disk where to find the plugin + name (str): postfix name of the plugin that is appended to each API + + Returns: + int: unique plugin id. If this id is negative, the plugin is not loaded. Once a plugin is loaded, you can + send commands to the plugin using `execute_plugin_commands` + """ + pass + + def execute_plugin_commands(self, plugin_id, *args, **kwargs): + """Execute the commands on the specified plugin. + + Args: + plugin_id (int): unique plugin id. + *args (list): list of argument values to be interpreted by the plugin. One can be a string, while the + others must be integers or float. + """ + pass + + def unload_plugin(self, plugin_id, *args, **kwargs): + """Unload the specified plugin from the simulator. + + Args: + plugin_id (int): unique plugin id. + """ + pass + + # loading URDFs, SDFs, MJCFs + + def load_urdf(self, filename, position, orientation, use_fixed_base=0, scale=1.0, *args, **kwargs): + """Load a URDF file in the simulator. + + Args: + filename (str): a relative or absolute path to the URDF file on the file system of the physics server. + position (vec3): create the base of the object at the specified position in world space coordinates [x,y,z] + orientation (quat): create the base of the object at the specified orientation as world space quaternion + [x,y,z,w] + use_fixed_base (bool): force the base of the loaded object to be static + scale (float): scale factor to the URDF model. + + Returns: + int (non-negative): unique id associated to the load model. + """ + pass + + def load_sdf(self, filename, scaling=1., *args, **kwargs): + """Load a SDF file in the simulator. + + Args: + filename (str): a relative or absolute path to the SDF file on the file system of the physics server. + scaling (float): scale factor for the object + + Returns: + list(int): list of object unique id for each object loaded + """ + pass + + def load_mjcf(self, filename, scaling=1., *args, **kwargs): + """Load a Mujoco file in the simulator. + + Args: + filename (str): a relative or absolute path to the MJCF file on the file system of the physics server. + scaling (float): scale factor for the object + + Returns: + list(int): list of object unique id for each object loaded + """ + pass + + def load_mesh(self, filename, position, orientation=(0, 0, 0, 1), mass=1., scale=(1., 1., 1.), color=None, + with_collision=True, flags=None, *args, **kwargs): + """Load a mesh into the simulator. + + Args: + filename (str): path to file for the mesh. Currently, only Wavefront .obj. It will create convex hulls + for each object (marked as 'o') in the .obj file. + position (float[3]): position of the mesh in the Cartesian world space (in meters) + orientation (float[4], np.quaternion): orientation of the mesh using quaternion. + If np.quaternion then it uses the convention (w,x,y,z). If float[4], it uses the convention (x,y,z,w) + mass (float): mass of the mesh (in kg). If mass = 0, it won't move even if there is a collision. + scale (float[3]): scale the mesh in the (x,y,z) directions + color (int[4], None): color of the mesh for red, green, blue, and alpha, each in range [0,1]. + with_collision (bool): If True, it will also create the collision mesh, and not only a visual mesh. + flags (int, None): if flag = `sim.GEOM_FORCE_CONCAVE_TRIMESH` (=1), this will create a concave static + triangle mesh. This should not be used with dynamic/moving objects, only for static (mass=0) terrain. + + Returns: + int: unique id of the mesh in the world + """ + pass + + @staticmethod + def get_available_sdfs(fullpath=False): + """Return the list of available SDFs in the simulator. + + Args: + fullpath (bool): If True, it will return the full path to the SDFs. If False, it will just return the + name of the SDF files (without the extension). + """ + return [] + + @staticmethod + def get_available_urdfs(fullpath=False): + """Return the list of available URDFs in the simulator. + + Args: + fullpath (bool): If True, it will return the full path to the URDFs. If False, it will just return the + name of the URDF files (without the extension). + """ + return [] + + @staticmethod + def get_available_mjcfs(fullpath=False): + """Return the list of available MJCFs in the simulator. + + Args: + fullpath (bool): If True, it will return the full path to the MJCFs. If False, it will just return the + name of the MJCF files (without the extension). + """ + return [] + + @staticmethod + def get_available_objs(fullpath=False): + """Return the list of available OBJs in the simulator. + + Args: + fullpath (bool): If True, it will return the full path to the OBJs. If False, it will just return the + name of the OBJ files (without the extension). + """ + return [] + + # bodies + + def create_body(self, visual_shape_id=-1, collision_shape_id=-1, mass=0., position=(0., 0., 0.), + orientation=(0., 0., 0., 1.), *args, **kwargs): + """Create a body in the simulator. + + Args: + visual_shape_id (int): unique id from createVisualShape or -1. You can reuse the visual shape (instancing) + collision_shape_id (int): unique id from createCollisionShape or -1. You can re-use the collision shape + for multiple multibodies (instancing) + mass (float): mass of the base, in kg (if using SI units) + position (np.float[3]): Cartesian world position of the base + orientation (np.float[4]): Orientation of base as quaternion [x,y,z,w] + + Returns: + int: non-negative unique id or -1 for failure. + """ + pass + + def remove_body(self, body_id): + """Remove a particular body in the simulator. + + Args: + body_id (int): unique body id. + """ + pass + + def num_bodies(self): + """Return the number of bodies present in the simulator. + + Returns: + int: number of bodies + """ + pass + + def get_body_info(self, body_id): + """Get the specified body information. + + Args: + body_id (int): unique body id. + + Returns: + dict, list: info + """ + pass + + def get_body_id(self, index): + """Get the body id associated to the index which is between 0 and `num_bodies()`. + + Args: + index (int): index between [0, `num_bodies()`] + + Returns: + int: unique body id. + """ + pass + + # constraint + + def create_constraint(self, parent_body_id, parent_link_id, child_body_id, child_link_id, joint_type, + joint_axis, parent_frame_position, child_frame_position, + parent_frame_orientation=(0., 0., 0., 1.), child_frame_orientation=(0., 0., 0., 1.), + *args, **kwargs): + """ + Create a constraint. + + Args: + parent_body_id (int): parent body unique id + parent_link_id (int): parent link index (or -1 for the base) + child_body_id (int): child body unique id, or -1 for no body (specify a non-dynamic child frame in world + coordinates) + child_link_id (int): child link index, or -1 for the base + joint_type (int): joint type: JOINT_PRISMATIC (=1), JOINT_FIXED (=4), JOINT_POINT2POINT (=5), + JOINT_GEAR (=6) + joint_axis (np.float[3]): joint axis, in child link frame + parent_frame_position (np.float[3]): position of the joint frame relative to parent CoM frame. + child_frame_position (np.float[3]): position of the joint frame relative to a given child CoM frame (or + world origin if no child specified) + parent_frame_orientation (np.float[4]): the orientation of the joint frame relative to parent CoM + coordinate frame + child_frame_orientation (np.float[4]): the orientation of the joint frame relative to the child CoM + coordinate frame (or world origin frame if no child specified) + + Returns: + int: constraint unique id. + """ + pass + + def remove_constraint(self, constraint_id): + """ + Remove the specified constraint. + + Args: + constraint_id (int): constraint unique id. + """ + pass + + def change_constraint(self, constraint_id, *args, **kwargs): + """ + Change the parameters of an existing constraint. + + Args: + constraint_id (int): constraint unique id. + """ + pass + + def num_constraints(self): + """ + Get the number of constraints created. + + Returns: + int: number of constraints created. + """ + pass + + def get_constraint_id(self, index): + """ + Get the constraint unique id associated with the index which is between 0 and `num_constraints()`. + + Args: + index (int): index between [0, `num_constraints()`] + + Returns: + int: constraint unique id. + """ + pass + + def get_constraint_info(self, constraint_id): + """ + Get information about the given constaint id. + + Args: + constraint_id (int): constraint unique id. + + Returns: + dict, list: info + """ + pass + + def get_constraint_state(self, constraint_id): + """ + Get the state of the given constraint. + + Args: + constraint_id (int): constraint unique id. + + Returns: + dict, list: state + """ + pass + + # objects + + def get_mass(self, body_id): + """ + Return the total mass of the robot (=sum of all mass links). + + Args: + body_id (int): unique object id, as returned from `load_urdf`. + + Returns: + float: total mass of the robot [kg] + """ + pass + + def get_base_mass(self, body_id): + """Return the base mass of the robot. + + Args: + body_id (int): unique object id. + """ + pass + + def get_base_name(self, body_id): + """ + Return the base name. + + Args: + body_id (int): unique object id. + + Returns: + str: base name + """ + pass + + def get_center_of_mass_position(self, body_id, link_ids=None): + """ + Return the center of mass position. + + Args: + body_id (int): unique body id. + link_ids (list of int): link ids associated with the given body id. If None, it will take all the links + of the specified body. + + Returns: + np.float[3]: center of mass position in the Cartesian world coordinates + """ + pass + + def get_center_of_mass_velocity(self, body_id, link_ids=None): + """ + Return the center of mass linear velocity. + + Args: + body_id (int): unique body id. + link_ids (list of int): link ids associated with the given body id. If None, it will take all the links + of the specified body. + + Returns: + np.float[3]: center of mass linear velocity. + """ + pass + + def get_base_pose(self, body_id): + """ + Get the current position and orientation of the base (or root link) of the body in Cartesian world coordinates. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[3]: base position + np.float[4]: base orientation (quaternion [x,y,z,w]) + """ + pass + + def get_base_position(self, body_id): + """ + Return the base position of the specified body. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[3]: base position. + """ + pass + + def get_base_orientation(self, body_id): + """ + Get the base orientation of the specified body. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[4]: base orientation in the form of a quaternion (x,y,z,w) + """ + pass + + def reset_base_pose(self, body_id, position, orientation): + """ + Reset the base position and orientation of the specified object id. + + Args: + body_id (int): unique object id. + position (np.float[3]): new base position. + orientation (np.float[4]): new base orientation (expressed as a quaternion [x,y,z,w]) + """ + pass + + def reset_base_position(self, body_id, position): + """ + Reset the base position of the specified body/object id while preserving its orientation. + + Args: + body_id (int): unique object id. + position (np.float[3]): new base position. + """ + pass + + def reset_base_orientation(self, body_id, orientation): + """ + Reset the base orientation of the specified body/object id while preserving its position. + + Args: + body_id (int): unique object id. + orientation (np.float[4]): new base orientation (expressed as a quaternion [x,y,z,w]) + """ + pass + + def get_base_velocity(self, body_id): + """ + Return the base linear and angular velocities. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[3]: linear velocity of the base in Cartesian world space coordinates + np.float[3]: angular velocity of the base in Cartesian world space coordinates + """ + pass + + def get_base_linear_velocity(self, body_id): + """ + Return the linear velocity of the base. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[3]: linear velocity of the base in Cartesian world space coordinates + """ + pass + + def get_base_angular_velocity(self, body_id): + """ + Return the angular velocity of the base. + + Args: + body_id (int): object unique id, as returned from `load_urdf`. + + Returns: + np.float[3]: angular velocity of the base in Cartesian world space coordinates + """ + pass + + def reset_base_velocity(self, body_id, linear_velocity=None, angular_velocity=None): + """ + Reset the base velocity. + + Args: + body_id (int): unique object id. + linear_velocity (np.float[3]): new linear velocity of the base. + angular_velocity (np.float[3]): new angular velocity of the base. + """ + pass + + def reset_base_linear_velocity(self, body_id, linear_velocity): + """ + Reset the base linear velocity. + + Args: + body_id (int): unique object id. + linear_velocity (np.float[3]): new linear velocity of the base + """ + pass + + def reset_base_angular_velocity(self, body_id, angular_velocity): + """ + Reset the base angular velocity. + + Args: + body_id (int): unique object id. + angular_velocity (np.float[3]): new angular velocity of the base + """ + pass + + def apply_external_force(self, body_id, link_id=-1, force=(0., 0., 0.), position=(0., 0., 0.), frame=1): + """ + Apply the specified external force on the specified position on the body / link. + + Args: + body_id (int): unique body id. + link_id (int): unique link id. If -1, it will be the base. + force (np.float[3]): external force to be applied. + position (np.float[3]): position on the link where the force is applied. See `flags` for coordinate + systems. If None, it is the center of mass of the body (or the link if specified). + frame (int): if frame = 1, then the force / position is described in the link frame. If frame = 2, they + are described in the world frame. + """ + pass + + def apply_external_torque(self, body_id, link_id=-1, torque=(0., 0., 0.), frame=1): + """ + Apply an external torque on a body, or a link of the body. Note that after each simulation step, the external + torques are cleared to 0. + + Args: + body_id (int): unique body id. + link_id (int): link id to apply the torque, if -1 it will apply the torque on the base + torque (float[3]): Cartesian torques to be applied on the body + frame (int): Specify the coordinate system of force/position: either `pybullet.WORLD_FRAME` (=2) for + Cartesian world coordinates or `pybullet.LINK_FRAME` (=1) for local link coordinates. + """ + pass + + # robots (joints and links) + + def num_joints(self, body_id): + """ + Return the total number of joints of the specified body. This is the same as calling `num_links`. + + Args: + body_id (int): unique body id. + + Returns: + int: number of joints with the associated body id. + """ + pass + + def num_actuated_joints(self, body_id): + """ + Return the total number of actuated joints associated with the given body id. + + Args: + body_id (int): unique body id. + + Returns: + int: number of actuated joints of the specified body. + """ + pass + + def num_links(self, body_id): + """ + Return the total number of links of the specified body. This is the same as calling `num_joints`. + + Args: + body_id (int): unique body id. + + Returns: + int: number of links with the associated body id. + """ + return self.num_joints(body_id) + + def get_joint_info(self, body_id, joint_id): + """ + Return information about the given joint about the specified body. + + Note that this method returns a lot of information, so specific methods have been implemented that return + only the desired information. Also, note that we do not convert the data here. + + Args: + body_id (int): unique body id. + joint_id (int): joint id is included in [0..`num_joints(body_id)`]. + + Returns: + dict, list: joint info + """ + pass + + def get_joint_state(self, body_id, joint_id): + """ + Get the joint state. + + Args: + body_id (int): unique body id. + joint_id (int): joint index in range [0..num_joints(body_id)] + + Returns: + float: The position value of this joint. + float: The velocity value of this joint. + np.float[6]: These are the joint reaction forces, if a torque sensor is enabled for this joint it is + [Fx, Fy, Fz, Mx, My, Mz]. Without torque sensor, it is [0, 0, 0, 0, 0, 0]. + float: This is the motor torque applied during the last stepSimulation. Note that this only applies in + VELOCITY_CONTROL and POSITION_CONTROL. If you use TORQUE_CONTROL then the applied joint motor torque + is exactly what you provide, so there is no need to report it separately. + """ + pass + + def get_joint_states(self, body_id, joint_ids): + """ + Get the joint state of the specified joints. + + Args: + body_id (int): unique body id. + joint_ids (list of int): list of joint ids. + + Returns: + list: + float: The position value of this joint. + float: The velocity value of this joint. + np.float[6]: These are the joint reaction forces, if a torque sensor is enabled for this joint it is + [Fx, Fy, Fz, Mx, My, Mz]. Without torque sensor, it is [0, 0, 0, 0, 0, 0]. + float: This is the motor torque applied during the last `step`. Note that this only applies in + VELOCITY_CONTROL and POSITION_CONTROL. If you use TORQUE_CONTROL then the applied joint motor + torque is exactly what you provide, so there is no need to report it separately. + """ + pass + + def reset_joint_state(self, body_id, joint_id, position, velocity=0.): + """ + Reset the state of the joint. It is best only to do this at the start, while not running the simulation: + `reset_joint_state` overrides all physics simulation. + + Args: + body_id (int): unique body id. + joint_id (int): joint index in range [0..num_joints(body_id)] + position (float): the joint position (angle in radians [rad] or position [m]) + velocity (float): the joint velocity (angular [rad/s] or linear velocity [m/s]) + """ + pass + + def enable_joint_force_torque_sensor(self, body_id, joint_ids, enable=True): + """ + You can enable or disable a joint force/torque sensor in each joint. + + Args: + body_id (int): body unique id. + joint_ids (int, int[N]): joint index in range [0..num_joints(body_id)], or list of joint ids. + enable (bool): True to enable, False to disable the force/torque sensor + """ + pass + + def set_joint_motor_control(self, body_id, joint_ids, control_mode=2, positions=None, + velocities=None, forces=None, kp=None, kd=None, max_velocity=None): + """ + Set the joint motor control. + + In position control: + .. math:: error = Kp (x_{des} - x) + Kd (\dot{x}_{des} - \dot{x}) + + In velocity control: + .. math:: error = \dot{x}_{des} - \dot{x} + + Note that the maximum forces and velocities are not automatically used for the different control schemes. + + Args: + body_id (int): body unique id. + joint_ids (int): joint/link id, or list of joint ids. + control_mode (int): POSITION_CONTROL (=2) (which is in fact CONTROL_MODE_POSITION_VELOCITY_PD), + VELOCITY_CONTROL (=0), TORQUE_CONTROL (=1) and PD_CONTROL (=3). + positions (float, np.float[N]): target joint position(s) (used in POSITION_CONTROL). + velocities (float, np.float[N]): target joint velocity(ies). In VELOCITY_CONTROL and POSITION_CONTROL, + the target velocity(ies) is(are) the desired velocity of the joint. Note that the target velocity(ies) + is(are) not the maximum joint velocity(ies). In PD_CONTROL and + POSITION_CONTROL/CONTROL_MODE_POSITION_VELOCITY_PD, the final target velocities are computed using: + `kp*(erp*(desiredPosition-currentPosition)/dt)+currentVelocity+kd*(m_desiredVelocity - currentVelocity)` + forces (float, list of float): in POSITION_CONTROL and VELOCITY_CONTROL, these are the maximum motor + forces used to reach the target values. In TORQUE_CONTROL these are the forces / torques to be applied + each simulation step. + kp (float, list of float): position (stiffness) gain(s) (used in POSITION_CONTROL). + kd (float, list of float): velocity (damping) gain(s) (used in POSITION_CONTROL). + max_velocity (float): in POSITION_CONTROL this limits the velocity to a maximum. + """ + pass + + def get_link_state(self, body_id, link_id, compute_velocity=False, compute_forward_kinematics=False): + """ + Get the state of the associated link. + + Args: + body_id (int): body unique id. + link_id (int): link index. + compute_velocity (bool): If True, the Cartesian world velocity will be computed and returned. + compute_forward_kinematics (bool): if True, the Cartesian world position/orientation will be recomputed + using forward kinematics. + + Returns: + np.float[3]: Cartesian position of CoM + np.float[4]: Cartesian orientation of CoM, in quaternion [x,y,z,w] + np.float[3]: local position offset of inertial frame (center of mass) expressed in the URDF link frame + np.float[4]: local orientation (quaternion [x,y,z,w]) offset of the inertial frame expressed in URDF link + frame + np.float[3]: world position of the URDF link frame + np.float[4]: world orientation of the URDF link frame + np.float[3]: Cartesian world linear velocity. Only returned if `compute_velocity` is True. + np.float[3]: Cartesian world angular velocity. Only returned if `compute_velocity` is True. + """ + pass + + def get_link_states(self, body_id, link_ids, compute_velocity=False, compute_forward_kinematics=False): + """ + Get the state of the associated links. + + Args: + body_id (int): body unique id. + link_ids (list of int): list of link index. + compute_velocity (bool): If True, the Cartesian world velocity will be computed and returned. + compute_forward_kinematics (bool): if True, the Cartesian world position/orientation will be recomputed + using forward kinematics. + + Returns: + list: + np.float[3]: Cartesian position of CoM + np.float[4]: Cartesian orientation of CoM, in quaternion [x,y,z,w] + np.float[3]: local position offset of inertial frame (center of mass) expressed in the URDF link frame + np.float[4]: local orientation (quaternion [x,y,z,w]) offset of the inertial frame expressed in URDF + link frame + np.float[3]: world position of the URDF link frame + np.float[4]: world orientation of the URDF link frame + np.float[3]: Cartesian world linear velocity. Only returned if `compute_velocity` is True. + np.float[3]: Cartesian world angular velocity. Only returned if `compute_velocity` is True. + """ + pass + + def get_link_names(self, body_id, link_ids): + """ + Return the name of the given link(s). + + Args: + body_id (int): unique body id. + link_ids (int, list of int): link id, or list of link ids. + + Returns: + if 1 link: + str: link name + if multiple links: + str[N]: link names + """ + pass + + def get_link_masses(self, body_id, link_ids): + """ + Return the mass of the given link(s). + + Args: + body_id (int): unique body id. + link_ids (int, list of int): link id, or list of link ids. + + Returns: + if 1 link: + float: mass of the given link + else: + float[N]: mass of each link + """ + pass + + def get_link_frames(self, body_id, link_ids): + pass + + def get_link_world_positions(self, body_id, link_ids): + """ + Return the CoM position (in the Cartesian world space coordinates) of the given link(s). + + Args: + body_id (int): unique body id. + link_ids (list of int): list of link indices. + + Returns: + if 1 link: + np.float[3]: the link CoM position in the world space + if multiple links: + np.float[N,3]: CoM position of each link in world space + """ + pass + + def get_link_positions(self, body_id, link_ids): + pass + + def get_link_world_orientations(self, body_id, link_ids): + """ + Return the CoM orientation (in the Cartesian world space) of the given link(s). + + Args: + body_id (int): unique body id. + link_ids (list of int): list of link indices. + + Returns: + if 1 link: + np.float[4]: Cartesian orientation of the link CoM (x,y,z,w) + if multiple links: + np.float[N,4]: CoM orientation of each link (x,y,z,w) + """ + pass + + def get_link_orientations(self, body_id, link_ids): + pass + + def get_link_world_linear_velocities(self, body_id, link_ids): + """ + Return the linear velocity of the link(s) expressed in the Cartesian world space coordinates. + + Args: + body_id (int): unique body id. + link_ids (list of int): list of link indices. + + Returns: + if 1 link: + np.float[3]: linear velocity of the link in the Cartesian world space + if multiple links: + np.float[N,3]: linear velocity of each link + """ + pass + + def get_link_world_angular_velocities(self, body_id, link_ids): + """ + Return the angular velocity of the link(s) in the Cartesian world space coordinates. + + Args: + body_id (int): unique body id. + link_ids (list of int): list of link indices. + + Returns: + if 1 link: + np.float[3]: angular velocity of the link in the Cartesian world space + if multiple links: + np.float[N,3]: angular velocity of each link + """ + pass + + def get_link_world_velocities(self, body_id, link_ids): + """ + Return the linear and angular velocities (expressed in the Cartesian world space coordinates) for the given + link(s). + + Args: + body_id (int): unique body id. + link_ids (list of int): list of link indices. + + Returns: + if 1 link: + np.float[6]: linear and angular velocity of the link in the Cartesian world space + if multiple links: + np.float[N,6]: linear and angular velocity of each link + """ + pass + + def get_link_velocities(self, body_id, link_ids): + pass + + def get_q_indices(self, body_id, joint_ids): + """ + Get the corresponding q index of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + int: q index + if multiple joints: + np.int[N]: q indices + """ + pass + + def get_actuated_joint_ids(self, body_id): + """ + Get the actuated joint ids associated with the given body id. + + Args: + body_id (int): unique body id. + + Returns: + list of int: actuated joint ids. + """ + pass + + def get_joint_names(self, body_id, joint_ids): + """ + Return the name of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + str: name of the joint + if multiple joints: + str[N]: name of each joint + """ + pass + + def get_joint_type_ids(self, body_id, joint_ids): + """ + Get the joint type ids. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + int: joint type id. + if multiple joints: list of above + """ + pass + + def get_joint_type_names(self, body_id, joint_ids): + """ + Get joint type names. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + str: joint type name. + if multiple joints: list of above + """ + pass + + def get_joint_dampings(self, body_id, joint_ids): + """ + Get the damping coefficient of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + float: damping coefficient of the given joint + if multiple joints: + np.float[N]: damping coefficient for each specified joint + """ + pass + + def get_joint_frictions(self, body_id, joint_ids): + """ + Get the friction coefficient of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + float: friction coefficient of the given joint + if multiple joints: + np.float[N]: friction coefficient for each specified joint + """ + pass + + def get_joint_limits(self, body_id, joint_ids): + """ + Get the joint limits of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + np.float[2]: lower and upper limit + if multiple joints: + np.float[N,2]: lower and upper limit for each specified joint + """ + pass + + def get_joint_max_forces(self, body_id, joint_ids): + """ + Get the maximum force that can be applied on the given joint(s). + + Warning: Note that this is not automatically used in position, velocity, or torque control. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + float: maximum force [N] + if multiple joints: + np.float[N]: maximum force for each specified joint [N] + """ + pass + + def get_joint_max_velocities(self, body_id, joint_ids): + """ + Get the maximum velocity that can be applied on the given joint(s). + + Warning: Note that this is not automatically used in position, velocity, or torque control. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + float: maximum velocity [rad/s] + if multiple joints: + np.float[N]: maximum velocities for each specified joint [rad/s] + """ + pass + + def get_joint_axes(self, body_id, joint_ids): + """ + Get the joint axis about the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + np.float[3]: joint axis + if multiple joint: + np.float[N,3]: list of joint axis + """ + pass + + def set_joint_positions(self, body_id, joint_ids, positions, velocities=None, kps=None, kds=None, forces=None): + """ + Set the position of the given joint(s) (using position control). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + positions (float, np.float[N]): desired position, or list of desired positions [rad] + velocities (None, float, np.float[N]): desired velocity, or list of desired velocities [rad/s] + kps (None, float, np.float[N]): position gain(s) + kds (None, float, np.float[N]): velocity gain(s) + forces (None, float, np.float[N]): maximum motor force(s)/torque(s) used to reach the target values. + """ + pass + + def get_joint_positions(self, body_id, joint_ids): + """ + Get the position of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + + Returns: + if 1 joint: + float: joint position [rad] + if multiple joints: + np.float[N]: joint positions [rad] + """ + pass + + def set_joint_velocities(self, body_id, joint_ids, velocities, max_force=None): + """ + Set the velocity of the given joint(s) (using velocity control). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + velocities (float, np.float[N]): desired velocity, or list of desired velocities [rad/s] + max_force (None, float, np.float[N]): maximum motor forces/torques + """ + pass + + def get_joint_velocities(self, body_id, joint_ids): + """ + Get the velocity of the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + + Returns: + if 1 joint: + float: joint velocity [rad/s] + if multiple joints: + np.float[N]: joint velocities [rad/s] + """ + pass + + def set_joint_accelerations(self, body_id, joint_ids, accelerations, q=None, dq=None): + """ + Set the acceleration of the given joint(s) (using force control). This is achieved by performing inverse + dynamic which given the joint accelerations compute the joint torques to be applied. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + accelerations (float, np.float[N]): desired joint acceleration, or list of desired joint accelerations + [rad/s^2] + """ + pass + + def get_joint_accelerations(self, body_id, joint_ids, q=None, dq=None): + """ + Get the acceleration at the given joint(s). This is carried out by first getting the joint torques, then + performing forward dynamics to get the joint accelerations from the joint torques. + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + q (list of int, None): all the joint positions. If None, it will compute it. + dq (list of int, None): all the joint velocities. If None, it will compute it. + + Returns: + if 1 joint: + float: joint acceleration [rad/s^2] + if multiple joints: + np.float[N]: joint accelerations [rad/s^2] + """ + pass + + def set_joint_torques(self, body_id, joint_ids, torques): + """ + Set the torque/force to the given joint(s) (using force/torque control). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): joint id, or list of joint ids. + torques (float, list of float): desired torque(s) to apply to the joint(s) [N]. + """ + pass + + def get_joint_torques(self, body_id, joint_ids): + """ + Get the applied torque(s) on the given joint(s). + + Args: + body_id (int): unique body id. + joint_ids (int, list of int): a joint id, or list of joint ids. + + Returns: + if 1 joint: + float: torque [Nm] + if multiple joints: + np.float[N]: torques associated to the given joints [Nm] + """ + pass + + def get_joint_reaction_forces(self, body_id, joint_ids): + """Return the joint reaction forces at the given joint. Note that the torque sensor must be enabled, otherwise + it will always return [0,0,0,0,0,0]. + + Args: + body_id (int): unique body id. + joint_ids (int, int[N]): joint id, or list of joint ids + + Returns: + if 1 joint: + np.float[6]: joint reaction force (fx,fy,fz,mx,my,mz) [N,Nm] + if multiple joints: + np.float[N,6]: joint reaction forces [N, Nm] + """ + pass + + def get_joint_powers(self, body_id, joint_ids): + """Return the applied power at the given joint(s). Power = torque * velocity. + + Args: + body_id (int): unique body id. + joint_ids (int, int[N]): joint id, or list of joint ids + + Returns: + if 1 joint: + float: joint power [W] + if multiple joints: + np.float[N]: power at each joint [W] + """ + pass + + # visualization + + def create_visual_shape(self, shape_type, radius=0.5, half_extents=(1., 1., 1.), length=1., filename=None, + mesh_scale=(1., 1., 1.), plane_normal=(0., 0., 1.), flags=-1, rgba_color=None, + specular_color=None, visual_frame_position=None, vertices=None, indices=None, uvs=None, + normals=None, visual_frame_orientation=None): + """ + Create a visual shape in the simulator. + + Args: + shape_type (int): type of shape; GEOM_SPHERE (=2), GEOM_BOX (=3), GEOM_CAPSULE (=7), GEOM_CYLINDER (=4), + GEOM_PLANE (=6), GEOM_MESH (=5) + radius (float): only for GEOM_SPHERE, GEOM_CAPSULE, GEOM_CYLINDER + half_extents (np.float[3], list/tuple of 3 floats): only for GEOM_BOX. + length (float): only for GEOM_CAPSULE, GEOM_CYLINDER (length = height). + filename (str): Filename for GEOM_MESH, currently only Wavefront .obj. Will create convex hulls for each + object (marked as 'o') in the .obj file. + mesh_scale (np.float[3], list/tuple of 3 floats): scale of mesh (only for GEOM_MESH). + plane_normal (np.float[3], list/tuple of 3 floats): plane normal (only for GEOM_PLANE). + flags (int): unused / to be decided + rgba_color (list/tuple of 4 floats): color components for red, green, blue and alpha, each in range [0..1]. + specular_color (list/tuple of 3 floats): specular reflection color, red, green, blue components in range + [0..1] + visual_frame_position (np.float[3]): translational offset of the visual shape with respect to the link frame + vertices (list of np.float[3]): Instead of creating a mesh from obj file, you can provide vertices, indices, + uvs and normals + indices (list of int): triangle indices, should be a multiple of 3. + uvs (list of np.float[2]): uv texture coordinates for vertices. Use changeVisualShape to choose the + texture image. The number of uvs should be equal to number of vertices + normals (list of np.float[3]): vertex normals, number should be equal to number of vertices. + visual_frame_orientation (np.float[4]): rotational offset (quaternion x,y,z,w) of the visual shape with + respect to the link frame + + Returns: + int: The return value is a non-negative int unique id for the visual shape or -1 if the call failed. + """ + pass + + def get_visual_shape_data(self, object_id, flags=-1): + """ + Get the visual shape data associated with the given object id. It will output a list of visual shape data. + + Args: + object_id (int): object unique id. + flags (int, None): VISUAL_SHAPE_DATA_TEXTURE_UNIQUE_IDS (=1) will also provide `texture_unique_id`. + + Returns: + list: + int: object unique id. + int: link index or -1 for the base + int: visual geometry type (TBD) + np.float[3]: dimensions (size, local scale) of the geometry + str: path to the triangle mesh, if any. Typically relative to the URDF, SDF or MJCF file location, but + could be absolute + np.float[3]: position of local visual frame, relative to link/joint frame + np.float[4]: orientation of local visual frame relative to link/joint frame + list of 4 floats: URDF color (if any specified) in Red / Green / Blue / Alpha + int: texture unique id of the shape or -1 if None. This field only exists if using + VISUAL_SHAPE_DATA_TEXTURE_UNIQUE_IDS (=1) flag. + """ + pass + + def change_visual_shape(self, object_id, link_id, shape_id=None, texture_id=None, rgba_color=None, + specular_color=None): + """ + Allows to change the texture of a shape, the RGBA color and other properties. + + Args: + object_id (int): unique object id. + link_id (int): link id. + shape_id (int): shape id. + texture_id (int): texture id. + rgba_color (float[4]): RGBA color. Each is in the range [0..1]. Alpha has to be 0 (invisible) or 1 + (visible) at the moment. + specular_color (int[3]): specular color components, RED, GREEN and BLUE, can be from 0 to large number + (>100). + """ + pass + + def load_texture(self, filename): + """ + Load a texture from file and return a non-negative texture unique id if the loading succeeds. + This unique id can be used with changeVisualShape. + + Args: + filename (str): path to the file. + + Returns: + int: texture unique id. If non-negative, the texture was loaded successfully. + """ + pass + + def compute_view_matrix(self, eye_position, target_position, up_vector): + """Compute the view matrix. + + The view matrix is the 4x4 matrix that maps the world coordinates into the camera coordinates. Basically, + it applies a rotation and translation such that the world is in front of the camera. That is, instead + of turning the camera to capture what we want in the world, we keep the camera fixed and turn the world. + + Args: + eye_position (np.float[3]): eye position in Cartesian world coordinates + target_position (np.float[3]): position of the target (focus) point in Cartesian world coordinates + up_vector (np.float[3]): up vector of the camera in Cartesian world coordinates + + Returns: + np.float[4,4]: the view matrix + """ + pass + + def compute_view_matrix_from_ypr(self, target_position, distance, yaw, pitch, roll, up_axis_index=2): + """Compute the view matrix from the yaw, pitch, and roll angles. + + The view matrix is the 4x4 matrix that maps the world coordinates into the camera coordinates. Basically, + it applies a rotation and translation such that the world is in front of the camera. That is, instead + of turning the camera to capture what we want in the world, we keep the camera fixed and turn the world. + + Args: + target_position (np.float[3]): target focus point in Cartesian world coordinates + distance (float): distance from eye to focus point + yaw (float): yaw angle in radians left/right around up-axis + pitch (float): pitch in radians up/down. + roll (float): roll in radians around forward vector + up_axis_index (int): either 1 for Y or 2 for Z axis up. + + Returns: + np.float[4,4]: the view matrix + """ + pass + + def compute_projection_matrix(self, left, right, bottom, top, near, far): + """Compute the orthographic projection matrix. + + The projection matrix is the 4x4 matrix that maps from the camera/eye coordinates to clipped coordinates. + It is applied after the view matrix. + + There are 2 projection matrices: + * orthographic projection + * perspective projection + + For the perspective projection, see `computeProjectionMatrixFOV(self)`. + + Args: + left (float): left screen (canvas) coordinate + right (float): right screen (canvas) coordinate + bottom (float): bottom screen (canvas) coordinate + top (float): top screen (canvas) coordinate + near (float): near plane distance + far (float): far plane distance + + Returns: + np.float[4,4]: the perspective projection matrix + """ + pass + + def compute_projection_matrix_fov(self, fov, aspect, near, far): + """Compute the perspective projection matrix using the field of view (FOV). + + Args: + fov (float): field of view + aspect (float): aspect ratio + near (float): near plane distance + far (float): far plane distance + + Returns: + np.float[4,4]: the perspective projection matrix + """ + pass + + def get_camera_image(self, width, height, view_matrix=None, projection_matrix=None, light_direction=None, + light_color=None, light_distance=None, shadow=None, light_ambient_coeff=None, + light_diffuse_coeff=None, light_specular_coeff=None, renderer=None, flags=None): + """ + The `get_camera_image` API will return a RGB image, a depth buffer and a segmentation mask buffer with body + unique ids of visible objects for each pixel. + + Args: + width (int): horizontal image resolution in pixels + height (int): vertical image resolution in pixels + view_matrix (np.float[4,4]): 4x4 view matrix, see `compute_view_matrix` + projection_matrix (np.float[4,4]): 4x4 projection matrix, see `compute_projection` + light_direction (np.float[3]): `light_direction` specifies the world position of the light source, + the direction is from the light source position to the origin of the world frame. + light_color (np.float[3]): directional light color in [RED,GREEN,BLUE] in range 0..1 + light_distance (float): distance of the light along the normalized `light_direction` + shadow (bool): True for shadows, False for no shadows + light_ambient_coeff (float): light ambient coefficient + light_diffuse_coeff (float): light diffuse coefficient + light_specular_coeff (float): light specular coefficient + renderer (int): renderer + flags (int): flags + + Returns: + int: width image resolution in pixels (horizontal) + int: height image resolution in pixels (vertical) + np.int[width, height, 4]: RBGA pixels (each pixel is in the range [0..255] for each channel R, G, B, A) + np.float[width, heigth]: Depth buffer. + np.int[width, height]: Segmentation mask buffer. For each pixels the visible object unique id. + """ + pass + + def get_rgba_image(self, width, height, view_matrix=None, projection_matrix=None, light_direction=None, + light_color=None, light_distance=None, shadow=None, light_ambient_coeff=None, + light_diffuse_coeff=None, light_specular_coeff=None, renderer=None, flags=None): + """ + The `get_rgba_image` API will return a RGBA image. + + Args: + width (int): horizontal image resolution in pixels + height (int): vertical image resolution in pixels + view_matrix (np.float[4,4]): 4x4 view matrix, see `compute_view_matrix` + projection_matrix (np.float[4,4]): 4x4 projection matrix, see `compute_projection` + light_direction (np.float[3]): `light_direction` specifies the world position of the light source, + the direction is from the light source position to the origin of the world frame. + light_color (np.float[3]): directional light color in [RED,GREEN,BLUE] in range 0..1 + light_distance (float): distance of the light along the normalized `light_direction` + shadow (bool): True for shadows, False for no shadows + light_ambient_coeff (float): light ambient coefficient + light_diffuse_coeff (float): light diffuse coefficient + light_specular_coeff (float): light specular coefficient + renderer (int): renderer. + flags (int): flags. + + Returns: + np.int[width, height, 4]: RBGA pixels (each pixel is in the range [0..255] for each channel R, G, B, A) + """ + pass + + def get_depth_image(self, width, height, view_matrix=None, projection_matrix=None, light_direction=None, + light_color=None, light_distance=None, shadow=None, light_ambient_coeff=None, + light_diffuse_coeff=None, light_specular_coeff=None, renderer=None, flags=None): + """ + The `get_depth_image` API will return a depth buffer. + + Args: + width (int): horizontal image resolution in pixels + height (int): vertical image resolution in pixels + view_matrix (np.float[4,4]): 4x4 view matrix, see `compute_view_matrix` + projection_matrix (np.float[4,4]): 4x4 projection matrix, see `compute_projection` + light_direction (np.float[3]): `light_direction` specifies the world position of the light source, + the direction is from the light source position to the origin of the world frame. + light_color (np.float[3]): directional light color in [RED,GREEN,BLUE] in range 0..1 + light_distance (float): distance of the light along the normalized `light_direction` + shadow (bool): True for shadows, False for no shadows + light_ambient_coeff (float): light ambient coefficient + light_diffuse_coeff (float): light diffuse coefficient + light_specular_coeff (float): light specular coefficient + renderer (int): renderer. + flags (int): flags. + + Returns: + np.float[width, heigth]: Depth buffer. + """ + pass + + def get_segmentation_image(self, width, height, view_matrix=None, projection_matrix=None, light_direction=None, + light_color=None, light_distance=None, shadow=None, light_ambient_coeff=None, + light_diffuse_coeff=None, light_specular_coeff=None, renderer=None, flags=None): + """ + The `get_segmentation_image` API will return a segmentation mask buffer with body unique ids of visible objects + for each pixel. + + Args: + width (int): horizontal image resolution in pixels + height (int): vertical image resolution in pixels + view_matrix (np.float[4,4]): 4x4 view matrix, see `compute_view_matrix` + projection_matrix (np.float[4,4]): 4x4 projection matrix, see `compute_projection` + light_direction (np.float[3]): `light_direction` specifies the world position of the light source, + the direction is from the light source position to the origin of the world frame. + light_color (np.float[3]): directional light color in [RED,GREEN,BLUE] in range 0..1 + light_distance (float): distance of the light along the normalized `light_direction` + shadow (bool): True for shadows, False for no shadows + light_ambient_coeff (float): light ambient coefficient + light_diffuse_coeff (float): light diffuse coefficient + light_specular_coeff (float): light specular coefficient + renderer (int): renderer + flags (int): flags + + Returns: + np.int[width, height]: Segmentation mask buffer. For each pixels the visible object unique id. + """ + pass + + # collisions + + def create_collision_shape(self, shape_type, radius=0.5, half_extents=(1., 1., 1.), height=1., filename=None, + mesh_scale=(1., 1., 1.), plane_normal=(0., 0., 1.), flags=-1, + collision_frame_position=None, collision_frame_orientation=None): + """ + Create collision shape in the simulator. + + Args: + shape_type (int): type of shape; GEOM_SPHERE (=2), GEOM_BOX (=3), GEOM_CAPSULE (=7), GEOM_CYLINDER (=4), + GEOM_PLANE (=6), GEOM_MESH (=5) + radius (float): only for GEOM_SPHERE, GEOM_CAPSULE, GEOM_CYLINDER + half_extents (np.float[3], list/tuple of 3 floats): only for GEOM_BOX. + height (float): only for GEOM_CAPSULE, GEOM_CYLINDER (length = height). + filename (str): Filename for GEOM_MESH, currently only Wavefront .obj. Will create convex hulls for each + object (marked as 'o') in the .obj file. + mesh_scale (np.float[3], list/tuple of 3 floats): scale of mesh (only for GEOM_MESH). + plane_normal (np.float[3], list/tuple of 3 floats): plane normal (only for GEOM_PLANE). + flags (int): unused / to be decided + collision_frame_position (np.float[3]): translational offset of the collision shape with respect to the + link frame + collision_frame_orientation (np.float[4]): rotational offset (quaternion x,y,z,w) of the collision shape + with respect to the link frame + + Returns: + int: The return value is a non-negative int unique id for the collision shape or -1 if the call failed. + """ + pass + + def get_collision_shape_data(self, object_id, link_id=-1): + """ + Get the collision shape data associated with the specified object id and link id. + + Args: + object_id (int): object unique id. + link_id (int): link index or -1 for the base. + + Returns: + int: object unique id. + int: link id. + int: geometry type; GEOM_BOX (=3), GEOM_SPHERE (=2), GEOM_CAPSULE (=7), GEOM_MESH (=5), GEOM_PLANE (=6) + np.float[3]: depends on geometry type: + for GEOM_BOX: extents, + for GEOM_SPHERE: dimensions[0] = radius, + for GEOM_CAPSULE and GEOM_CYLINDER: dimensions[0] = height (length), dimensions[1] = radius. + For GEOM_MESH: dimensions is the scaling factor. + str: Only for GEOM_MESH: file name (and path) of the collision mesh asset. + np.float[3]: Local position of the collision frame with respect to the center of mass/inertial frame + np.float[4]: Local orientation of the collision frame with respect to the inertial frame + """ + pass + + def get_overlapping_objects(self, aabb_min, aabb_max): + """ + This query will return all the unique ids of objects that have Axis Aligned Bounding Box (AABB) overlap with + a given axis aligned bounding box. Note that the query is conservative and may return additional objects that + don't have actual AABB overlap. This happens because the acceleration structures have some heuristic that + enlarges the AABBs a bit (extra margin and extruded along the velocity vector). + + Args: + aabb_min (np.float[3]): minimum coordinates of the aabb + aabb_max (np.float[3]): maximum coordinates of the aabb + + Returns: + list of int: list of object unique ids. + """ + pass + + def get_aabb(self, body_id, link_id=-1): + """ + You can query the axis aligned bounding box (in world space) given an object unique id, and optionally a link + index. (when you don't pass the link index, or use -1, you get the AABB of the base). + + Args: + body_id (int): object unique id as returned by creation methods + link_id (int): link index in range [0..`getNumJoints(..)] + + Returns: + np.float[3]: minimum coordinates of the axis aligned bounding box + np.float[3]: maximum coordinates of the axis aligned bounding box + """ + pass + + def get_contact_points(self, body1, body2=None, link1_id=None, link2_id=None): + """ + Returns the contact points computed during the most recent call to `step`. + + Args: + body1 (int): only report contact points that involve body A + body2 (int, None): only report contact points that involve body B. Important: you need to have a valid + body A if you provide body B + link1_id (int, None): only report contact points that involve link index of body A + link2_id (int, None): only report contact points that involve link index of body B + + Returns: + list: + int: contact flag (reserved) + int: body unique id of body A + int: body unique id of body B + int: link index of body A, -1 for base + int: link index of body B, -1 for base + np.float[3]: contact position on A, in Cartesian world coordinates + np.float[3]: contact position on B, in Cartesian world coordinates + np.float[3]: contact normal on B, pointing towards A + float: contact distance, positive for separation, negative for penetration + float: normal force applied during the last `step` + float: lateral friction force in the first lateral friction direction (see next returned value) + np.float[3]: first lateral friction direction + float: lateral friction force in the second lateral friction direction (see next returned value) + np.float[3]: second lateral friction direction + """ + pass + + def get_closest_points(self, body1, body2, distance, link1_id=None, link2_id=None): + """ + Computes the closest points, independent from `step`. This also lets you compute closest points of objects + with an arbitrary separating distance. In this query there will be no normal forces reported. + + Args: + body1 (int): only report contact points that involve body A + body2 (int): only report contact points that involve body B. Important: you need to have a valid body A + if you provide body B + distance (float): If the distance between objects exceeds this maximum distance, no points may be returned. + link1_id (int): only report contact points that involve link index of body A + link2_id (int): only report contact points that involve link index of body B + + Returns: + list: + int: contact flag (reserved) + int: body unique id of body A + int: body unique id of body B + int: link index of body A, -1 for base + int: link index of body B, -1 for base + np.float[3]: contact position on A, in Cartesian world coordinates + np.float[3]: contact position on B, in Cartesian world coordinates + np.float[3]: contact normal on B, pointing towards A + float: contact distance, positive for separation, negative for penetration + float: normal force applied during the last `step`. Always equal to 0. + float: lateral friction force in the first lateral friction direction (see next returned value) + np.float[3]: first lateral friction direction + float: lateral friction force in the second lateral friction direction (see next returned value) + np.float[3]: second lateral friction direction + """ + pass + + def ray_test(self, from_position, to_position): + """ + Performs a single raycast to find the intersection information of the first object hit. + + Args: + from_position (np.float[3]): start of the ray in world coordinates + to_position (np.float[3]): end of the ray in world coordinates + + Returns: + list: + int: object unique id of the hit object + int: link index of the hit object, or -1 if none/parent + float: hit fraction along the ray in range [0,1] along the ray. + np.float[3]: hit position in Cartesian world coordinates + np.float[3]: hit normal in Cartesian world coordinates + """ + pass + + def ray_test_batch(self, from_positions, to_positions, parent_object_id=None, parent_link_id=None): + """Perform a batch of raycasts to find the intersection information of the first objects hit. + + This is similar to the ray_test, but allows you to provide an array of rays, for faster execution. The size of + 'rayFromPositions' needs to be equal to the size of 'rayToPositions'. You can one ray result per ray, even if + there is no intersection: you need to use the objectUniqueId field to check if the ray has hit anything: if + the objectUniqueId is -1, there is no hit. In that case, the 'hit fraction' is 1. + + Args: + from_positions (np.array[N,3]): list of start points for each ray, in world coordinates + to_positions (np.array[N,3]): list of end points for each ray in world coordinates + parent_object_id (int): ray from/to is in local space of a parent object + parent_link_id (int): ray from/to is in local space of a parent object + + Returns: + list: + int: object unique id of the hit object + int: link index of the hit object, or -1 if none/parent + float: hit fraction along the ray in range [0,1] along the ray. + np.float[3]: hit position in Cartesian world coordinates + np.float[3]: hit normal in Cartesian world coordinates + """ + pass + + def set_collision_filter_group_mask(self, body_id, link_id, filter_group, filter_mask): + """ + Enable/disable collision detection between groups of objects. Each body is part of a group. It collides with + other bodies if their group matches the mask, and vise versa. The following check is performed using the group + and mask of the two bodies involved. It depends on the collision filter mode. + + Args: + body_id (int): unique id of the body to be configured + link_id (int): link index of the body to be configured + filter_group (int): bitwise group of the filter + filter_mask (int): bitwise mask of the filter + """ + pass + + def set_collision_filter_pair(self, body1, body2, link1=-1, link2=-1, enable=True): + """ + Enable/disable collision between two bodies/links. + + Args: + body1 (int): unique id of body A to be filtered + body2 (int): unique id of body B to be filtered, A==B implies self-collision + link1 (int): link index of body A + link2 (int): link index of body B + enable (bool): True to enable collision, False to disable collision + """ + pass + + # kinematics and dynamics + + def get_dynamics_info(self, body_id, link_id=-1): + """ + Get dynamic information about the mass, center of mass, friction and other properties of the base and links. + + Args: + body_id (int): body/object unique id. + link_id (int): link/joint index or -1 for the base. + + Returns: + float: mass in kg + float: lateral friction coefficient + np.float[3]: local inertia diagonal. Note that links and base are centered around the center of mass and + aligned with the principal axes of inertia. + np.float[3]: position of inertial frame in local coordinates of the joint frame + np.float[4]: orientation of inertial frame in local coordinates of joint frame + float: coefficient of restitution + float: rolling friction coefficient orthogonal to contact normal + float: spinning friction coefficient around contact normal + float: damping of contact constraints. -1 if not available. + float: stiffness of contact constraints. -1 if not available. + """ + pass + + def change_dynamics(self, body_id, link_id=-1, mass=None, lateral_friction=None, spinning_friction=None, + rolling_friction=None, restitution=None, linear_damping=None, angular_damping=None, + contact_stiffness=None, contact_damping=None, friction_anchor=None, + local_inertia_diagonal=None, joint_damping=None): + """ + Change dynamic properties of the given body (or link) such as mass, friction and restitution coefficients, etc. + + Args: + body_id (int): object unique id, as returned by `load_urdf`, etc. + link_id (int): link index or -1 for the base. + mass (float): change the mass of the link (or base for link index -1) + lateral_friction (float): lateral (linear) contact friction + spinning_friction (float): torsional friction around the contact normal + rolling_friction (float): torsional friction orthogonal to contact normal + restitution (float): bouncyness of contact. Keep it a bit less than 1. + linear_damping (float): linear damping of the link (0.04 by default) + angular_damping (float): angular damping of the link (0.04 by default) + contact_stiffness (float): stiffness of the contact constraints, used together with `contact_damping` + contact_damping (float): damping of the contact constraints for this body/link. Used together with + `contact_stiffness`. This overrides the value if it was specified in the URDF file in the contact + section. + friction_anchor (int): enable or disable a friction anchor: positional friction correction (disabled by + default, unless set in the URDF contact section) + local_inertia_diagonal (np.float[3]): diagonal elements of the inertia tensor. Note that the base and + links are centered around the center of mass and aligned with the principal axes of inertia so there + are no off-diagonal elements in the inertia tensor. + joint_damping (float): joint damping coefficient applied at each joint. This coefficient is read from URDF + joint damping field. Keep the value close to 0. + `joint_damping_force = -damping_coefficient * joint_velocity`. + """ + pass + + def calculate_jacobian(self, body_id, link_id, local_position, q, dq, des_ddq): + """ + Return the full geometric Jacobian matrix :math:`J(q) = [J_{lin}(q), J_{ang}(q)]^T`, such that: + + .. math:: v = [\dot{p}, \omega]^T = J(q) \dot{q} + + where :math:`\dot{p}` is the Cartesian linear velocity of the link, and :math:`\omega` is its angular velocity. + + Warnings: if we have a floating base then the Jacobian will also include columns corresponding to the root + link DoFs (at the beginning). If it is a fixed base, it will only have columns associated with the joints. + + Args: + body_id (int): unique body id. + link_id (int): link id. + local_position (np.float[3]): the point on the specified link to compute the Jacobian (in link local + coordinates around its center of mass). If None, it will use the CoM position (in the link frame). + q (np.float[N]): joint positions of size N, where N is the number of DoFs. + dq (np.float[N]): joint velocities of size N, where N is the number of DoFs. + des_ddq (np.float[N]): desired joint accelerations of size N. + + Returns: + np.float[6,N], np.float[6,(6+N)]: full geometric (linear and angular) Jacobian matrix. The number of + columns depends if the base is fixed or floating. + """ + pass + + def calculate_mass_matrix(self, body_id, q): + """ + Return the mass/inertia matrix :math:`H(q)`, which is used in the rigid-body equation of motion (EoM) in joint + space given by (see [1]): + + .. math:: \tau = H(q)\ddot{q} + C(q,\dot{q}) + + where :math:`\tau` is the vector of applied torques, :math:`H(q)` is the inertia matrix, and + :math:`C(q,\dot{q}) \dot{q}` is the vector accounting for Coriolis, centrifugal forces, gravity, and any + other forces acting on the system except the applied torques :math:`\tau`. + + Warnings: If the base is floating, it will return a [6+N,6+N] inertia matrix, where N is the number of actuated + joints. If the base is fixed, it will return a [N,N] inertia matrix + + Args: + body_id (int): body unique id. + q (np.float[N]): joint positions of size N, where N is the total number of DoFs. + + Returns: + np.float[N,N], np.float[6+N,6+N]: inertia matrix + """ + pass + + def calculate_inverse_kinematics(self, body_id, link_id, position, orientation=None, lower_limits=None, + upper_limits=None, joint_ranges=None, rest_poses=None, joint_dampings=None, + solver=None, q_curr=None, max_iters=None, threshold=None): + """ + Compute the FULL Inverse kinematics; it will return a position for all the actuated joints. + + "You can compute the joint angles that makes the end-effector reach a given target position in Cartesian world + space. Internally, Bullet uses an improved version of Samuel Buss Inverse Kinematics library. At the moment + only the Damped Least Squares method with or without Null Space control is exposed, with a single end-effector + target. Optionally you can also specify the target orientation of the end effector. In addition, there is an + option to use the null-space to specify joint limits and rest poses. This optional null-space support requires + all 4 lists (lower_limits, upper_limits, joint_ranges, rest_poses), otherwise regular IK will be used." [1] + + Args: + body_id (int): body unique id, as returned by `load_urdf`, etc. + link_id (int): end effector link index. + position (np.float[3]): target position of the end effector (its link coordinate, not center of mass + coordinate!). By default this is in Cartesian world space, unless you provide `q_curr` joint angles. + orientation (np.float[4]): target orientation in Cartesian world space, quaternion [x,y,w,z]. If not + specified, pure position IK will be used. + lower_limits (np.float[N], list of N floats): lower joint limits. Optional null-space IK. + upper_limits (np.float[N], list of N floats): upper joint limits. Optional null-space IK. + joint_ranges (np.float[N], list of N floats): range of value of each joint. + rest_poses (np.float[N], list of N floats): joint rest poses. Favor an IK solution closer to a given rest + pose. + joint_dampings (np.float[N], list of N floats): joint damping factors. Allow to tune the IK solution using + joint damping factors. + solver (int): p.IK_DLS (=0) or p.IK_SDLS (=1), Damped Least Squares or Selective Damped Least Squares, as + described in the paper by Samuel Buss "Selectively Damped Least Squares for Inverse Kinematics". + q_curr (np.float[N]): list of joint positions. By default PyBullet uses the joint positions of the body. + If provided, the target_position and targetOrientation is in local space! + max_iters (int): maximum number of iterations. Refine the IK solution until the distance between target + and actual end effector position is below this threshold, or the `max_iters` is reached. + threshold (float): residual threshold. Refine the IK solution until the distance between target and actual + end effector position is below this threshold, or the `max_iters` is reached. + + Returns: + np.float[N]: joint positions (for each actuated joint). + """ + pass + + def calculate_inverse_dynamics(self, body_id, q, dq, des_ddq): + r""" + Starting from the specified joint positions :math:`q` and velocities :math:`\dot{q}`, it computes the joint + torques :math:`\tau` required to reach the desired joint accelerations :math:`\ddot{q}_{des}`. That is, + :math:`\tau = ID(model, q, \dot{q}, \ddot{q}_{des})`. + + Specifically, it uses the rigid-body equation of motion in joint space given by (see [1]): + + .. math:: \tau = H(q)\ddot{q} + C(q,\dot{q}) + + where :math:`\tau` is the vector of applied torques, :math:`H(q)` is the inertia matrix, and + :math:`C(q,\dot{q}) \dot{q}` is the vector accounting for Coriolis, centrifugal forces, gravity, and any + other forces acting on the system except the applied torques :math:`\tau`. + + Normally, a more popular form of this equation of motion (in joint space) is given by: + + .. math:: H(q) \ddot{q} + S(q,\dot{q}) \dot{q} + g(q) = \tau + J^T(q) F + + which is the same as the first one with :math:`C = S\dot{q} + g(q) - J^T(q) F`. However, this last formulation + is useful to understand what happens when we set some variables to 0. + Assuming that there are no forces acting on the system, and giving desired joint accelerations of 0, this + method will return :math:`\tau = S(q,\dot{q}) \dot{q} + g(q)`. If in addition joint velocities are also 0, + it will return :math:`\tau = g(q)` which can for instance be useful for gravity compensation. + + For forward dynamics, which computes the joint accelerations given the joint positions, velocities, and + torques (that is, :math:`\ddot{q} = FD(model, q, \dot{q}, \tau)`, this can be computed using + :math:`\ddot{q} = H^{-1} (\tau - C)` (see also `computeFullFD`). For more information about different + control schemes (position, force, impedance control and others), or about the formulation of the equation + of motion in task/operational space (instead of joint space), check the references [1-4]. + + Args: + body_id (int): body unique id. + q (np.float[N]): joint positions + dq (np.float[N]): joint velocities + des_ddq (np.float[N]): desired joint accelerations + + Returns: + np.float[N]: joint torques computed using the rigid-body equation of motion + + References: + [1] "Rigid Body Dynamics Algorithms", Featherstone, 2008, chap1.1 + [2] "Robotics: Modelling, Planning and Control", Siciliano et al., 2010 + [3] "Springer Handbook of Robotics", Siciliano et al., 2008 + [4] Lecture on "Impedance Control" by Prof. De Luca, Universita di Roma, + http://www.diag.uniroma1.it/~deluca/rob2_en/15_ImpedanceControl.pdf + """ + pass + + def calculate_forward_dynamics(self, body_id, q, dq, torques): + r""" + Given the specified joint positions :math:`q` and velocities :math:`\dot{q}`, and joint torques :math:`\tau`, + it computes the joint accelerations :math:`\ddot{q}`. That is, :math:`\ddot{q} = FD(model, q, \dot{q}, \tau)`. + + Specifically, it uses the rigid-body equation of motion in joint space given by (see [1]): + + .. math:: \ddot{q} = H(q)^{-1} (\tau - C(q,\dot{q})) + + where :math:`\tau` is the vector of applied torques, :math:`H(q)` is the inertia matrix, and + :math:`C(q,\dot{q}) \dot{q}` is the vector accounting for Coriolis, centrifugal forces, gravity, and any + other forces acting on the system except the applied torques :math:`\tau`. + + Normally, a more popular form of this equation of motion (in joint space) is given by: + + .. math:: H(q) \ddot{q} + S(q,\dot{q}) \dot{q} + g(q) = \tau + J^T(q) F + + which is the same as the first one with :math:`C = S\dot{q} + g(q) - J^T(q) F`. However, this last formulation + is useful to understand what happens when we set some variables to 0. + Assuming that there are no forces acting on the system, and giving desired joint torques of 0, this + method will return :math:`\ddot{q} = - H(q)^{-1} (S(q,\dot{q}) \dot{q} + g(q))`. If in addition + the joint velocities are also 0, it will return :math:`\ddot{q} = - H(q)^{-1} g(q)` which are + the accelerations due to gravity. + + For inverse dynamics, which computes the joint torques given the joint positions, velocities, and + accelerations (that is, :math:`\tau = ID(model, q, \dot{q}, \ddot{q})`, this can be computed using + :math:`\tau = H(q)\ddot{q} + C(q,\dot{q})`. For more information about different + control schemes (position, force, impedance control and others), or about the formulation of the equation + of motion in task/operational space (instead of joint space), check the references [1-4]. + + Args: + body_id (int): unique body id. + q (np.float[N]): joint positions + dq (np.float[N]): joint velocities + torques (np.float[N]): desired joint torques + + Returns: + np.float[N]: joint accelerations computed using the rigid-body equation of motion + + References: + [1] "Rigid Body Dynamics Algorithms", Featherstone, 2008, chap1.1 + [2] "Robotics: Modelling, Planning and Control", Siciliano et al., 2010 + [3] "Springer Handbook of Robotics", Siciliano et al., 2008 + [4] Lecture on "Impedance Control" by Prof. De Luca, Universita di Roma, + http://www.diag.uniroma1.it/~deluca/rob2_en/15_ImpedanceControl.pdf + """ + pass + + # debug + + def add_user_debug_line(self, from_pos, to_pos, rgb_color=None, width=None, lifetime=None, parent_object_id=None, + parent_link_id=None, line_id=None): + """Add a user debug line in the simulator. + + You can add a 3d line specified by a 3d starting point (from) and end point (to), a color [red,green,blue], + a line width and a duration in seconds. + + Args: + from_pos (np.float[3]): starting point of the line in Cartesian world coordinates + to_pos (np.float[3]): end point of the line in Cartesian world coordinates + rgb_color (np.float[3]): RGB color (each channel in range [0,1]) + width (float): line width (limited by OpenGL implementation). + lifetime (float): use 0 for permanent line, or positive time in seconds (afterwards the line with be + removed automatically) + parent_object_id (int): draw line in local coordinates of a parent object. + parent_link_id (int): draw line in local coordinates of a parent link. + line_id (int): replace an existing line item (to avoid flickering of remove/add). + + Returns: + int: unique user debug line id. + """ + pass + + def add_user_debug_text(self, text, position, rgb_color=None, size=None, lifetime=None, orientation=None, + parent_object_id=None, parent_link_id=None, text_id=None): + """ + Add 3D text at a specific location using a color and size. + + Args: + text (str): text. + position (np.float[3]): 3d position of the text in Cartesian world coordinates. + rgb_color (list/tuple of 3 floats): RGB color; each component in range [0..1] + size (float): text size + lifetime (float): use 0 for permanent text, or positive time in seconds (afterwards the text with be + removed automatically) + orientation (np.float[4]): By default, debug text will always face the camera, automatically rotation. + By specifying a text orientation (quaternion), the orientation will be fixed in world space or local + space (when parent is specified). Note that a different implementation/shader is used for camera + facing text, with different appearance: camera facing text uses bitmap fonts, text with specified + orientation uses TrueType font. + parent_object_id (int): draw text in local coordinates of a parent object. + parent_link_id (int): draw text in local coordinates of a parent link. + text_id (int): replace an existing text item (to avoid flickering of remove/add). + + Returns: + int: unique user debug text id. + """ + pass + + def add_user_debug_parameter(self, name, min_range, max_range, start_value): + """ + Add custom sliders to tune parameters. + + Args: + name (str): name of the parameter. + min_range (float): minimum value. + max_range (float): maximum value. + start_value (float): starting value. + + Returns: + int: unique user debug parameter id. + """ + pass + + def read_user_debug_parameter(self, parameter_id): + """ + Read the value of the parameter / slider. + + Args: + parameter_id: unique user debug parameter id. + + Returns: + float: reading of the parameter. + """ + pass + + def remove_user_debug_item(self, item_id): + """ + Remove the specified user debug item (line, text, parameter) from the simulator. + + Args: + item_id (int): unique id of the debug item to be removed (line, text etc) + """ + pass + + def remove_all_user_debug_items(self): + """ + Remove all user debug items from the simulator. + """ + pass + + def set_debug_object_color(self, object_id, link_id, rgb_color=(1, 0, 0)): + """ + Override the color of a specific object and link. + + Args: + object_id (int): unique object id. + link_id (int): link id. + rgb_color (float[3]): RGB debug color. + """ + pass + + def add_user_data(self, object_id, key, value): + """ + Add user data (at the moment text strings) attached to any link of a body. You can also override a previous + given value. You can add multiple user data to the same body/link. + + Args: + object_id (int): unique object/link id. + key (str): key string. + value (str): value string. + + Returns: + int: user data id. + """ + pass + + def num_user_data(self, object_id): + """ + Return the number of user data associated with the specified object/link id. + + Args: + object_id (int): unique object/link id. + + Returns: + int: the number of user data + """ + pass + + def get_user_data(self, user_data_id): + """ + Get the specified user data value. + + Args: + user_data_id (int): unique user data id. + + Returns: + str: value string. + """ + pass + + def get_user_data_id(self, object_id, key): + """ + Get the specified user data id. + + Args: + object_id (int): unique object/link id. + key (str): key string. + + Returns: + int: user data id. + """ + pass + + def get_user_data_info(self, object_id, index): + """ + Get the user data info associated with the given object and index. + + Args: + object_id (int): unique object id. + index (int): index (should be between [0, self.num_user_data(object_id)]). + + Returns: + int: user data id. + str: key. + int: body id. + int: link index + int: visual shape index. + """ + pass + + def remove_user_data(self, user_data_id): + """ + Remove the specified user data. + + Args: + user_data_id (int): user data id. + """ + pass + + def sync_user_data(self): + """ + Synchronize the user data. + """ + pass + + def configure_debug_visualizer(self, flag, enable): + """Configure the debug visualizer camera. + + Configure some settings of the built-in OpenGL visualizer, such as enabling or disabling wireframe, + shadows and GUI rendering. + + Args: + flag (int): The feature to enable or disable, such as + COV_ENABLE_WIREFRAME (=3): show/hide the collision wireframe + COV_ENABLE_SHADOWS (=2): show/hide shadows + COV_ENABLE_GUI (=1): enable/disable the GUI + COV_ENABLE_VR_PICKING (=5): enable/disable VR picking + COV_ENABLE_VR_TELEPORTING (=4): enable/disable VR teleporting + COV_ENABLE_RENDERING (=7): enable/disable rendering + COV_ENABLE_TINY_RENDERER (=12): enable/disable tiny renderer + COV_ENABLE_VR_RENDER_CONTROLLERS (=6): render VR controllers + COV_ENABLE_KEYBOARD_SHORTCUTS (=9): enable/disable keyboard shortcuts + COV_ENABLE_MOUSE_PICKING (=10): enable/disable mouse picking + COV_ENABLE_Y_AXIS_UP (Z is default world up axis) (=11): enable/disable Y axis up + COV_ENABLE_RGB_BUFFER_PREVIEW (=13): enable/disable RGB buffer preview + COV_ENABLE_DEPTH_BUFFER_PREVIEW (=14): enable/disable Depth buffer preview + COV_ENABLE_SEGMENTATION_MARK_PREVIEW (=15): enable/disable segmentation mark preview + enable (bool): False (disable) or True (enable) + """ + pass + + def get_debug_visualizer(self): + """Get information about the debug visualizer camera. + + Returns: + float: width of the visualizer camera + float: height of the visualizer camera + np.float[4,4]: view matrix [4,4] + np.float[4,4]: perspective projection matrix [4,4] + np.float[3]: camera up vector expressed in the Cartesian world space + np.float[3]: forward axis of the camera expressed in the Cartesian world space + np.float[3]: This is a horizontal vector that can be used to generate rays (for mouse picking or creating + a simple ray tracer for example) + np.float[3]: This is a vertical vector that can be used to generate rays (for mouse picking or creating a + simple ray tracer for example) + float: yaw angle (in radians) of the camera, in Cartesian local space coordinates + float: pitch angle (in radians) of the camera, in Cartesian local space coordinates + float: distance between the camera and the camera target + np.float[3]: target of the camera, in Cartesian world space coordinates + """ + pass + + def reset_debug_visualizer(self, distance, yaw, pitch, target_position): + """Reset the debug visualizer camera. + + Reset the 3D OpenGL debug visualizer camera distance (between eye and camera target position), camera yaw and + pitch and camera target position + + Args: + distance (float): distance from eye to camera target position + yaw (float): camera yaw angle (in radians) left/right + pitch (float): camera pitch angle (in radians) up/down + target_position (np.float[3]): target focus point of the camera + """ + pass + + # events (mouse, keyboard) + + def get_keyboard_events(self): + """Get the key events. + + Returns: + dict: {keyId: keyState} + * `keyID` is an integer (ascii code) representing the key. Some special keys like shift, arrows, + and others are are defined in pybullet such as `B3G_SHIFT`, `B3G_LEFT_ARROW`, `B3G_UP_ARROW`,... + * `keyState` is an integer. 3 if the button has been pressed, 1 if the key is down, 2 if the key has + been triggered. + """ + pass + + def get_mouse_events(self): + """Get the mouse events. + + Returns: + list of mouse events: + eventType (int): 1 if the mouse is moving, 2 if a button has been pressed or released + mousePosX (float): x-coordinates of the mouse pointer + mousePosY (float): y-coordinates of the mouse pointer + buttonIdx (int): button index for left/middle/right mouse button. It is -1 if nothing, + 0 if left button, 1 if scroll wheel (pressed), 2 if right button + buttonState (int): 0 if nothing, 3 if the button has been pressed, 4 is the button has been released, + 1 if the key is down (never observed), 2 if the key has been triggered (never + observed). + """ + pass + + def get_mouse_and_keyboard_events(self): + """Get the mouse and key events. + + Returns: + list: list of mouse events + dict: dictionary of key events + """ + pass diff --git a/pyrobolearn/simulators/simulator.py b/pyrobolearn/simulators/simulator.py index ec17b1c..47c04db 100644 --- a/pyrobolearn/simulators/simulator.py +++ b/pyrobolearn/simulators/simulator.py @@ -7,7 +7,7 @@ in PyBullet [1,2], but in accordance with the PEP8 style guide [3]. Because the simulator is based on the PyBullet API and we want all the simulator APIs to be similar, all the other simulators would have to be able to carry out operations such as querying the state of the robots, kinematics and -dynamics, . +dynamics, etc. Dependencies in PRL: None diff --git a/pyrobolearn/values/nn_value.py b/pyrobolearn/values/nn_value.py index 01b4f86..b9e9af4 100644 --- a/pyrobolearn/values/nn_value.py +++ b/pyrobolearn/values/nn_value.py @@ -110,7 +110,7 @@ class MLPValue(ValueNetwork): This is defined by :math:`V_{\psi}(s_t)` where the function :math:`V` is approximated by a multilayer perceptron. """ - def __init__(self, state, hidden_units=(), activation_fct='linear', last_activation_fct=None, dropout_prob=None, + def __init__(self, state, hidden_units=(), activation='linear', last_activation=None, dropout=None, preprocessors=None): """Initialize the Value MLP approximator. @@ -118,19 +118,18 @@ class MLPValue(ValueNetwork): state (State): 1D-states that is feed to the policy (the input dimensions will be inferred from the states) hidden_units (list/tuple of int): number of hidden units in the corresponding layer - activation_fct (None, str, or list/tuple of str/None): activation function to be applied after each layer. + activation (None, str, or list/tuple of str/None): activation function to be applied after each layer. If list/tuple, then it has to match the - last_activation_fct (None or str): last activation function to be applied. If not specified, it will check + last_activation (None or str): last activation function to be applied. If not specified, it will check if it is in the list/tuple of activation functions provided for the previous argument. - dropout_prob (None, float, or list/tuple of float/None): dropout probability. + dropout (None, float, or list/tuple of float/None): dropout probability. preprocessors ((list of) Processor): pre-processors to be applied on the input state before being fed to the inner model / function approximator. """ output = torch.Tensor([1.]) # torch.Tensor([[1.]]) - model = MLPApproximator(state, output, hidden_units=hidden_units, activation=activation_fct, - last_activation=last_activation_fct, dropout=dropout_prob, - preprocessors=preprocessors) + model = MLPApproximator(state, output, hidden_units=hidden_units, activation=activation, + last_activation=last_activation, dropout=dropout, preprocessors=preprocessors) super(MLPValue, self).__init__(state, model) @@ -142,8 +141,8 @@ class MLPQValue(QValueNetwork): and outputs the value :math:`Q(s,a)`. This can be used for continuous actions as well as discrete actions. """ - def __init__(self, state, action, hidden_units=(), activation_fct='linear', last_activation_fct=None, - dropout_prob=None, preprocessors=None): + def __init__(self, state, action, hidden_units=(), activation='linear', last_activation=None, dropout=None, + preprocessors=None): """ Initialize the MLP state-action value function approximator. @@ -151,18 +150,18 @@ class MLPQValue(QValueNetwork): state (State): input state. action (Action): input action. hidden_units (list/tuple of int): number of hidden units in the corresponding layer - activation_fct (None, str, or list/tuple of str/None): activation function to be applied after each layer. + activation (None, str, or list/tuple of str/None): activation function to be applied after each layer. If list/tuple, then it has to match the - last_activation_fct (None or str): last activation function to be applied. If not specified, it will check + last_activation (None or str): last activation function to be applied. If not specified, it will check if it is in the list/tuple of activation functions provided for the previous argument. - dropout_prob (None, float, or list/tuple of float/None): dropout probability. + dropout (None, float, or list/tuple of float/None): dropout probability. preprocessors ((list of) Processor): pre-processors to be applied on the input state before being fed to the inner model / function approximator. """ model = MLPApproximator(inputs=[state, action], outputs=torch.Tensor([1]), hidden_units=hidden_units, - activation=activation_fct, last_activation=last_activation_fct, - dropout=dropout_prob, preprocessors=preprocessors) + activation=activation, last_activation=last_activation, dropout=dropout, + preprocessors=preprocessors) super(MLPQValue, self).__init__(state, action, model=model) @@ -175,8 +174,8 @@ class MLPQValueOutput(ParametrizedQValueOutput): :math:`Q(s,a)` for each discrete action. This can NOT be used with continuous actions. """ - def __init__(self, state, action, hidden_units=(), activation_fct='linear', last_activation_fct=None, - dropout_prob=None, preprocessors=None): + def __init__(self, state, action, hidden_units=(), activation='linear', last_activation=None, dropout=None, + preprocessors=None): """ Initialize the MLP state-action value function approximator. @@ -184,16 +183,15 @@ class MLPQValueOutput(ParametrizedQValueOutput): state (State): input state. action (Action): output action. hidden_units (list/tuple of int): number of hidden units in the corresponding layer - activation_fct (None, str, or list/tuple of str/None): activation function to be applied after each layer. + activation (None, str, or list/tuple of str/None): activation function to be applied after each layer. If list/tuple, then it has to match the - last_activation_fct (None or str): last activation function to be applied. If not specified, it will check + last_activation (None or str): last activation function to be applied. If not specified, it will check if it is in the list/tuple of activation functions provided for the previous argument. - dropout_prob (None, float, or list/tuple of float/None): dropout probability. + dropout (None, float, or list/tuple of float/None): dropout probability. preprocessors ((list of) Processor): pre-processors to be applied on the input state before being fed to the inner model / function approximator. """ - model = MLPApproximator(inputs=state, outputs=action, hidden_units=hidden_units, - activation=activation_fct, last_activation=last_activation_fct, - dropout=dropout_prob, preprocessors=preprocessors) + model = MLPApproximator(inputs=state, outputs=action, hidden_units=hidden_units, activation=activation, + last_activation=last_activation, dropout=dropout, preprocessors=preprocessors) super(MLPQValueOutput, self).__init__(state, action, model=model)