Journal article

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

Mo Chen, Sylvia L Herbert, Haimin Hu, Ye Pu, Jaime Fernandez Fisac, Somil Bansal, SooJean Han, Claire J Tomlin

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2021

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 erro..

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University of Melbourne Researchers

Grants

Awarded by ONR under the Embedded Humans MURI Project


Funding Acknowledgements

This work was supported by ONR under the Embedded Humans MURI Project under Grant N0001416-1-2206. 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.