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IROS
2007
IEEE

Collision detection in legged locomotion using supervised learning

11 years 6 months ago
Collision detection in legged locomotion using supervised learning
Abstract— We propose a fast approach for detecting collisionfree swing-foot trajectories for legged locomotion over extreme terrains. Instead of simulating the swing trajectories and checking for collisions along them, our approach uses machine learning techniques to predict whether a swing trajectory is collision-free. Using a set of local terrain features, we apply supervised learning to train a classifier to predict collisions. Both in simulation and on a real quadruped platform, our results show that our classifiers can improve the accuracy of collision detection compared to a real-time geometric approach without significantly increasing the computation time.
Finale Doshi, Emma Brunskill, Alexander C. Shkolni
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IROS
Authors Finale Doshi, Emma Brunskill, Alexander C. Shkolnik, Thomas Kollar, Khashayar Rohanimanesh, Russ Tedrake, Nicholas Roy
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