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28 lines
1.7 KiB
HTML
28 lines
1.7 KiB
HTML
<h1>PyRoboLearn</h1>
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<p>Abstract: "On the quest for building autonomous robots, several robot learning frameworks with different functionalities have
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recently been developed. Yet, frameworks that combine diverse learning paradigms (such as imitation and reinforcement learning)
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into a common place are scarce. Existing ones tend to be robot-specific, and often require time-consuming work to be used with
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other robots.
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Also, their architecture is often weakly structured, mainly because of a lack of modularity and flexibility. This leads users
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to reimplement several pieces of code to integrate them into their own experimental or benchmarking work.
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To overcome these issues, we introduce PyRoboLearn, a new Python robot learning framework that combines different learning
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paradigms into a single framework. Our framework provides a plethora of robotic environments, learning models and algorithms.
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PyRoboLearn is developed with a particular focus on modularity, flexibility, generality, and simplicity to favor (re)usability.
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This is achieved by abstracting each key concept, undertaking a modular programming approach, minimizing the coupling among the
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different modules, and favoring composition over inheritance for better flexibility. We demonstrate the different features and
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utility of our framework through different use cases."</p>
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<ul>
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<li>Link to paper: arxiv </li>
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<li>Link to Github repository: https://github.com/robotlearn/pyrobolearn </li>
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<li>Link to documentation: doc </li>
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<li>Link to videos: youtube </li>
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<li>Link to <a href="https://github.com/robotlearn/pyrobolearn/tree/master/examples">examples</a></li>
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</ul>
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<!--h2>Simulators</h2>
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<h2>Worlds</h2>
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<h2>Robots</h2>
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<h2>Interfaces</h2-->
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