Reachability-guided sampling for planning under differential constraints
Name
Shkolnik-2009-Reachability-guided sampling for planning under differential constraints.pdf
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Author(s)
Shkolnik, Alexander C.
Walter, Matthew R.
Tedrake, Russell Louis
Date Issued
July 2009
Journal
IEEE International Conference on Robotics and Automation, 2009. ICRA '09
Publisher
Institute of Electrical and Electronics Engineers
Citation
Shkolnik, A., M. Walter, and R. Tedrake. “Reachability-guided sampling for planning under differential constraints.” Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. 2009. 2859-2865. ©2009 IEEE.
Version
Final published version
Abstract
Rapidly-exploring random trees (RRTs) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency of these algorithms can be severely compromised in the presence of certain kinodynamics constraints. Obstacle fields with tunnels, or tubes are notoriously difficult, as are systems with differential constraints, because the tree grows inefficiently at the boundaries. Here we present a new sampling strategy for the RRT algorithm, based on an estimated feasibility set, which affords a dramatic improvement in performance in these severely constrained systems. We demonstrate the algorithm with a detailed look at the expansion of an RRT in a swing up task, and on path planning for a nonholonomic car.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ROBOT.2009.5152874
