Chance Constrained Motion Planning for High-Dimensional Robots

Chance Constrained Motion Planning for High-Dimensional Robots

© 2019 IEEE. This paper introduces Probabilistic Chekov (p-Chekov), a chance-constrained motion planning system that can be applied to high degree-of-freedom (DOF) robots under motion uncertainty and imperfect state information. Given process and observation noise models, it can find feasible trajec...

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Bibliographic Details
Main Authors: Dai, Siyu (Author), Schaffert, Shawn (Author), Jasour, Ashkan (Author), Hofmann, Andreas (Author), Williams, Brian C (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-11-04T14:59:04Z.
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