Coordinated Task Assignment and Path Planning with Trajectory Optimization for Multi-agent Systems

Abstract In this paper, we propose a holistic method for coordinated task assignment and trajectory generation for multi-agent systems in a known environment. First, we propose CBS-TS that generates conflict-free paths for each robot, while ensuring all the goal locations are visited. CBS-TS conducts the best-first search over a conflict forest, which is guaranteed to be optimal and complete. Then, the resulting paths are optimized to dynamically feasible trajectories. Through optimization constraints, the smoothed trajectory remains conflict-free and ensures all goal locations are precisely visited. We provide extensive simulation results to analyze the computational efficiency of the proposed algorithm and conduct physical experiments with heterogeneous robots to demonstrate the feasibility of generated trajectories.