Programming by demonstration: removing sub-optimal actions in a partially known configuration space

Programming by demonstration is a promising approach to automatic robot programming, however, methods are required to remove suboptimal actions that can be demonstrated by end users. In this paper we use the partial knowledge of configuration space (C-space) derived in the previous work by Chen et al. (2000) to remove suboptimal actions from a demonstration. Our idea is to use demonstrated paths to predict what regions in C-space are obstacle free. Suboptimal actions in a demonstration are then avoided by planning alternative actions that pass through the obstacle free regions. Experimental results show the validity of the approach. A demonstrated path containing significant sub-optimality was converted by the approach into a short, efficient path suitable for execution by the robot.

[1]  Nathan Delson,et al.  Robot programming by human demonstration: adaptation and inconsistency in constrained motion , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[2]  Rüdiger Dillmann,et al.  Building elementary robot skills from human demonstration , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[3]  B. Faverjon,et al.  Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .

[4]  Richard A. Volz,et al.  Learning force-based assembly skills from human demonstration for execution in unstructured environments , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[5]  Roger W. Brockett,et al.  Hybrid Models for Motion Control Systems , 1993 .

[6]  H. Harry Asada,et al.  The Discrete Event Modeling and Trajectory Planning of Robotic Assembly Tasks , 1995 .

[7]  Joris De Schutter,et al.  Derivation of compliant motion programs based on human demonstration , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[8]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[9]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..