diff --git a/pyrobolearn/filters/utils.py b/pyrobolearn/filters/utils.py
new file mode 100644
index 0000000..98ce013
--- /dev/null
+++ b/pyrobolearn/filters/utils.py
@@ -0,0 +1,33 @@
+#!/usr/bin/env python
+"""Common filters used in signal processing
+
+These filters can be useful to smooth signal trajectories.
+"""
+
+from scipy.signal import butter, lfilter
+
+
+__author__ = "Brian Delhaisse"
+__copyright__ = "Copyright 2018, PyRoboLearn"
+__credits__ = ["Brian Delhaisse"]
+__license__ = "GNU GPLv3"
+__version__ = "1.0.0"
+__maintainer__ = "Brian Delhaisse"
+__email__ = "briandelhaisse@gmail.com"
+__status__ = "Development"
+
+
+# Butterworth Filter
+# Example from http://scipy-cookbook.readthedocs.io/items/ButterworthBandpass.html
+def butter_bandpass(lowcut, highcut, fs, order=5):
+    nyq = 0.5 * fs
+    low = lowcut / nyq
+    high = highcut / nyq
+    b, a = butter(order, [low, high], btype='band')
+    return b, a
+
+
+def butter_bandpass_filter(data, lowcut, highcut, fs, order=5):
+    b, a = butter_bandpass(lowcut, highcut, fs, order=order)
+    y = lfilter(b, a, data)
+    return y