FaSTrack: a Modular Framework for Fast and Guaranteed Safe Motion Planning. Fast and safe navigation of dynamical systems through a priori unknown cluttered environments is vital to many applications of autonomous systems. However, trajectory planning for autonomous systems is computationally intensive, often requiring simplified dynamics that sacrifice safety and dynamic feasibility in order to plan efficiently. Conversely, safe trajectories can be computed using more sophisticated dynamic models, but this is typically too slow to be used for real-time planning. We propose a new algorithm FaSTrack: Fast and Safe Tracking for High Dimensional systems. A path or trajectory planner using simplified dynamics to plan quickly can be incorporated into the FaSTrack framework, which provides a safety controller for the vehicle along with a guaranteed tracking error bound. This bound captures all possible deviations due to high dimensional dynamics and external disturbances. Note that FaSTrack is modular and can be used with most current path or trajectory planners. We demonstrate this framework using a 10D nonlinear quadrotor model tracking a 3D path obtained from an RRT planner.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Barbosa, Fernando S.; Karlsson, Jesper; Tajvar, Pouria; Tumova, Jana: Formal methods for robot motion planning with time and space constraints (extended abstract) (2021)
- Chen, Mo; Herbert, Sylvia L.; Hu, Haimin; Pu, Ye; Fisac, Jaime Fernández; Bansal, Somil; Han, Soojean; Tomlin, Claire J.: FaSTrack: a modular framework for real-time motion planning and guaranteed safe tracking (2021)
- Fan, Chuchu; Miller, Kristina; Mitra, Sayan: Fast and guaranteed safe controller synthesis for nonlinear vehicle models (2020)
- Ghosh, Shromona; Bansal, Somil; Sangiovanni-Vincentelli, Alberto; Seshia, Sanjit A.; Tomlin, Claire: A new simulation metric to determine safe environments and controllers for systems with unknown dynamics (2019)