Multi-Agent Path Planning and Trajectory Generation for Confined Environments

Planning the collision-free, simultaneous movement of multiple agents is a fundamental problem in multirobot systems and becomes particularly challenging in highly confined environments. This paper addresses this problem by first searching for collision-free paths in a discretized environment and then optimizing the agents' dynamically feasible trajectories along the discrete paths with respect to energy and time. Our approach extends the available movement options at each planning step of the enhanced conflict-based search and results in shorter path lengths, faster planning times, and reduced number of waiting events for agents at waypoints. We compare our new approach with the original algorithm in a simulation study and investigate the performance in confined spaces.