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arXiv · 2412.21180

STITCHER: Real-Time Trajectory Planning with Motion Primitive Search

Helene J. Levy·Brett T. Lopez
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Abstract

Autonomous high-speed navigation through large, complex environments requires real-time generation of agile trajectories that are dynamically feasible, collision-free, and satisfy constraints. Most modern trajectory planning techniques rely on numerical optimization because high-quality, expressive trajectories that satisfy constraints can be systematically computed. However, strict requirements on computation time and the risk of numerical instability can limit the use of optimization-based planners in safety-critical situations. This work presents an optimization-free planning framework called STITCHER that leverages graph search to generate long-range trajectories by stitching short trajectory segments together in real time. STITCHER is shown to outperform modern optimization-based planners through its innovative planning architecture and several algorithmic developments that make real-time planning possible. Simulation results show safe trajectories through complex environments can be generated in milliseconds that cover tens of meters.

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Helene J. Levy, Brett T. Lopez. 2024-12-30. STITCHER: Real-Time Trajectory Planning with Motion Primitive Search. https://arxiv.org/abs/2412.21180

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