Safe and complete trajectory generation for robot teams with higher-order dynamics

Sarah Tang, Vijay Kumar

Abstract: In this work, we consider the labeled multi-robot planning problem. In this paradigm, a team of robots at fixed start positions must navigate to pre-specified and noninterchangable goal positions. While many algorithms have been proposed for finding optimal solutions to this problem, most methods assume that the robots are kinematic agents, whereas in reality, robots often have high-order dynamics that must be respected by their trajectories. Here, we propose a centralized method for generating trajectories for teams of robots with general nth-order dynamics navigating to labeled goals. Our algorithm is safe and complete and additionally allows for decoupled optimization of each robot's trajectory as a Quadratic Program with linear constraints. We present simulation results for teams of up to 20 robots.