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This article presents a multi-robot trajectory planning method which not onlyguarantees optimization feasibility and but also resolves deadlocks inobstacle-dense environments. The method is proposed via formulating a recursiveoptimization problem, where a novel safe corridor is generated online to ensureobstacle avoidance in trajectory planning. A dynamic-priority mechanism iscombined with the right-hand rule to handle potential deadlocks that are muchharder to resolve due to static obstacles. Comparisons with otherstate-of-the-art results are conducted to validate the improved safety andsuccess rate. Additional hardware experiments are carried out with up to eightnano-quadrotors in various cluttered scenarios.

Multi-Robot Trajectory Planning with Feasibility Guarantee and Deadlock Resolution: An Obstacle-Dense Environment