Robust Sampling-based Motion Planning with Asymptotic Optimality Guarantees
This paper presents a novel sampling-based planner, CC-RRT*, which generates robust, asymptotically optimal trajectories in real-time for linear Gaussian systems subject to process noise, localization error, and uncertain environmental constraints. CC-RRT* provides guaranteed probabilistic feasibili...
Main Authors: | Karaman, Sertac (Contributor), How, Jonathan P. (Contributor), Luders, Brandon Douglas (Contributor) |
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Other Authors: | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor) |
Format: | Article |
Language: | English |
Published: |
American Institute of Aeronautics and Astronautics,
2013-10-21T15:27:20Z.
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Subjects: | |
Online Access: | Get fulltext |
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