Graph-based trajectory planning through programming by demonstration
As robots are utilized in a growing number of applications, the ability to teach them to perform tasks safely and accurately becomes ever more critical. Programming by demonstration offers an expressive means for teaching while being accessible to domain experts who may be novices in robotics. This...
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| Published in: | 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 1929 - 1936 |
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| Main Authors: | , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.10.2012
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| Subjects: | |
| ISBN: | 1467317373, 9781467317375 |
| ISSN: | 2153-0858 |
| Online Access: | Get full text |
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| Summary: | As robots are utilized in a growing number of applications, the ability to teach them to perform tasks safely and accurately becomes ever more critical. Programming by demonstration offers an expressive means for teaching while being accessible to domain experts who may be novices in robotics. This work investigates a programming by demon- stration approach to learning motion trajectories for robotic manipulator tasks. Using a graph constructed to determine correspondences between multiple imperfect demonstrations, the robot learner plans novel trajectories that safely and smoothly generalize the teacher's behavior, while attenuating those imperfections. The learner also actively detects instances of diverging strategy between examples, requesting advice for resolving these ambiguities. We demonstrate our approach in example domains with a 7 degree-of-freedom manipulator. |
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| ISBN: | 1467317373 9781467317375 |
| ISSN: | 2153-0858 |
| DOI: | 10.1109/IROS.2012.6386101 |