Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alternative is to rely on a high-level planner, but the generic symbolic representations used are not well suited to particular robot executions. Contrarily, motion primitives encode robot motions in a way that can be easily adapted to different situations. This paper presents a combined framework that exploits the advantages of both approaches. The number of required symbolic states is reduced, as motion primitives provide
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CitationCanal, G., Pignat, E., Alenyà, G., Calinon, Torras, C. Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance. A: IEEE International Conference on Robotics and Automation. "2018 IEEE International Conference on Mechatronics, Robotics and Automation : ICMRA 2018 : May 18-21, 2018, Hefei University of Technology, China". Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 3273-3278.