AMSwarmX: Safe Swarm Coordination in CompleX Environments Via Implicit Non-Convex Decomposition of the Obstacle-Free Space

Quadrotor motion planning in complex environ- ments leverage the concept of safe flight corridor (SFC) to facilitate static obstacle avoidance. Typically, SFCs are con- structed through convex decomposition of the environment’s free space into cuboids, convex polyhedra, or spheres. However, such SFCs can be overly conservative when dealing with a quadrotor swarm, substantially limiting the available free space for quadrotors to coordinate. This paper presents an Alternating Minimization-based approach that does not require building a conservative free-space approximation. Instead, both static and dynamic collision constraints are treated in a unified manner. Dynamic collisions are handled based on shared position trajectories of the quadrotors. Static obstacle avoidance is coupled with distance queries from the Octomap, providing an implicit non-convex decomposition of free space. As a result, our approach is scalable to arbitrary complex environments. Through extensive comparisons in simulation, we demonstrate a 60% improvement in success rate, an average 1.8× reduction in mission completion time, and an average 23× reduction in per-agent computation time compared to SFC-based ap- proaches. We also experimentally validated our approach using a Crazyflie quadrotor swarm of up to 12 quadrotors in obstacle- rich environments. The code, supplementary materials, and videos are released for reference.