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We present a scalable and effective multi-agent safe motion planner thatenables a group of agents to move to their desired locations while avoidingcollisions with obstacles and other agents, with the presence of richobstacles, high-dimensional, nonlinear, nonholonomic dynamics, actuationlimits, and disturbances. We address this problem by finding a piecewise linearpath for each agent such that the actual trajectories following these paths areguaranteed to satisfy the reach-and-avoid requirement. We show that the spatialtracking error of the actual trajectories of the controlled agents can bepre-computed for any qualified path that considers the minimum duration of eachpath segment due to actuation limits. Using these bounds, we find acollision-free path for each agent by solving Mixed Integer-Linear Programs andcoordinate agents by using the priority-based search. We demonstrate our methodby benchmarking in 2D and 3D scenarios with ground vehicles and quadrotors,respectively, and show improvements over the solving time and the solutionquality compared to two state-of-the-art multi-agent motion planners.

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances