Interactive generation of flexible robot programs

Service robots require interactive programming interfaces that allow users without programming experience to easily instruct the robots. Systems following the programming by demonstration (PbD) paradigm that were developed within the last years are getting closer to this goal. However, most of these systems lack the possibility for the user to supervise and alter the course of program generation after the initial demonstration was performed. In this paper we present an approach, where the user is able to supervise the entire program generation process and to annotate, and edit system hypotheses. Moreover, the knowledge representation and algorithms presented enable the user to generalize the generated program by annotating conditions and object selection criteria via a 3D simulation and graphical user interface. The resulting PbD-system widens the PbD approach in robotics to the interactive generation of flexible robot programs based on demonstration and annotations.

[1]  Masayuki Inaba,et al.  Learning by watching: extracting reusable task knowledge from visual observation of human performance , 1994, IEEE Trans. Robotics Autom..

[2]  Katsushi Ikeuchi,et al.  A grasp abstraction hierarchy for recognition of grasping tasks from observation , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[3]  Rüdiger Dillmann,et al.  Robot Programming by Demonstration (RPD): Supporting the Induction by Human Interaction , 1996, Machine Learning.

[4]  Rüdiger Dillmann,et al.  3D-icon based user interaction for robot programming by demonstration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[5]  Mark R. Cutkosky,et al.  On grasp choice, grasp models, and the design of hands for manufacturing tasks , 1989, IEEE Trans. Robotics Autom..

[6]  Tomoichi Takahashi Time normalization and analysis method in robot programming from human demonstration data , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[7]  Thomas Knieriemen Autonome mobile Roboter - Sensordateninterpretation und Weltmodellierung zur Navigation in unbekannter Umgebung , 1991 .

[8]  Rüdiger Dillmann,et al.  Integrating skills into multi-agent systems , 1998, J. Intell. Manuf..

[9]  Katsushi Ikeuchi,et al.  Towards an assembly plan from observation. I. Assembly task recognition using face-contact relations (polyhedral objects) , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[10]  Katsushi Ikeuchi,et al.  Modelling planar assembly tasks: representation and recognition , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.