Multi-Agent Motion Planning with Bézier Curve Optimization under Kinodynamic Constraints (Extended Abstract)

Jingtian Yan, Jiaoyang Li

Abstract: Multi-Agent Motion Planning (MAMP) is a problem that seeks collision-free dynamically-feasible trajectories for multiple moving agents in a known environment while minimizing their travel time. In this paper, we introduce a three-level planner called PSB that combines search-based and optimization-based techniques to address the challenges posed by MAMP. PSB fully considers the kinodynamic capability of the agents and produces solutions with smooth speed profiles. Empirically, we evaluate PSB within the domain of obstacle-rich grid map navigation for mobile robots. PSB shows up to 49.79% improvements in solution cost compared to existing methods while achieving significant improvement in scalability.