A probabilistic roadmap planner for flexible objects with a workspace medial-axis-based sampling approach
- 20 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 254-259
- https://doi.org/10.1109/iros.1999.813013
Abstract
Probabilistic roadmap planners have been used with success to plan paths for flexible objects such as metallic plates or plastic flexible pipes. This paper improves the performance of these planners by using the medial axis of the workspace to guide the random sampling. At a preprocessing stage, the me- dial axis of the workspace is computed using a recent efficien t algorithm. Then the flexible object is fitted at random points along the medial axis. The energy of all generated configura- tions is minimized and the planner proceeds to connect them with low-energy quasi-static paths in a roadmap that captur es the connectivity of the free space. Given an initial and a fina l configuration, the planner connects these to the roadmap and searches the roadmap for a path. Our experimental results show that the new sampling scheme is successful in identify- ing critical deformations of the object along solution path s which results in a significant reduction of the computation time. Our work on planning for flexible objects has applica- tions in industrial settings, virtual reality environment s, and medicine.Keywords
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