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Published December 2021 | Accepted Version
Journal Article Open

FaSTrack: A Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

Abstract

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified planning model of the system. The plan is tracked by the system, represented by a more realistic, higher dimensional tracking model . We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton–Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs.

Additional Information

© 2021 IEEE. Manuscript received October 11, 2019; revised August 10, 2020; accepted December 4, 2020. Date of publication February 16, 2021; date of current version December 3, 2021. This work was supported by ONR under the Embedded Humans MURI Project under Grant N00014-16-1-2206. The work of Sylvia L. Herbert was supported in part by the National Science Foundation Graduate Research Fellowship Program and in part by the UC Berkeley Chancellor's Fellowship Program. This article was presented in part at the IEEE 56th Annual Conference on Decision and Control, Melbourne Convention Center, Melbourne, VIC, Australia, December 2017. Recommended by Associate Editor H. Lin.

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Created:
August 20, 2023
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October 23, 2023