TR2020-089
Motion-Planning for Unicycles using the Invariant-Set Motion-Planner
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- "Motion-Planning for Unicycles using the Invariant-Set Motion-Planner", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147919, June 2020, pp. 1235-1240.BibTeX TR2020-089 PDF
- @inproceedings{Danielson2020jun2,
- author = {Danielson, Claus and Berntorp, Karl and Di Cairano, Stefano and Weiss, Avishai},
- title = {Motion-Planning for Unicycles using the Invariant-Set Motion-Planner},
- booktitle = {American Control Conference (ACC)},
- year = 2020,
- pages = {1235--1240},
- month = jun,
- publisher = {IEEE},
- doi = {10.23919/ACC45564.2020.9147919},
- issn = {2378-5861},
- isbn = {978-1-5386-8266-1},
- url = {https://www.merl.com/publications/TR2020-089}
- }
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- "Motion-Planning for Unicycles using the Invariant-Set Motion-Planner", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147919, June 2020, pp. 1235-1240.
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MERL Contacts:
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Research Area:
Abstract:
This paper adapts the invariant-set motion-planner to systems with unicycle-like dynamics. The invariant-set motion-planner is a motion-planning algorithm that uses the positive-invariant sets of the closed-loop dynamics to find a collision-free path to a desired target through an obstacle filled environment. The main challenge in applying the invariant-set motion-planner to unicycles is that the positive invariant sets of the unicycle under discontinuous feedback control have complex geometry. Thus, we develop numerically efficient mathematical tools for detecting collisions. We demonstrate the invariant-set motion-planner for unicycles in an automated perpendicular parking case study.
Related News & Events
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NEWS MERL researchers presented 10 papers at American Control Conference (ACC) Date: July 1, 2020 - July 3, 2020
Where: Denver, Colorado (virtual)
MERL Contacts: Mouhacine Benosman; Ankush Chakrabarty; Stefano Di Cairano; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference, MERL presented 10 papers on subjects including autonomous-vehicle decision making and motion planning, nonlinear estimation for thermal-fluid models and GNSS positioning, learning-based reference governors and reference governors for railway vehicles, and fail-safe rendezvous control.