Distributed Optimal Formation Transformation Control of UAV Swarms in Cluttered Environments

This paper presents a hierarchical framework for distributed optimal formation transformation control of unmanned aerial vehicle (UAV) swarms in cluttered environments. The framework decouples the problem into high-level assignment and low-level motion planning. First, we introduced the distributed incremental Hungarian-based assignment (DIHBA) algorithm, a communication-efficient method that achieves globally optimal assignments without a central coordinator. For motion planning, a lightweight planner uses a pre-computed library of time-optimal, dynamically feasible trajectories, enabling rapid, safe and formation awareness online selection. Comprehensive simulations demonstrate that framework achieves globally optimal assignments for swarms of up to 200 UAVs with communication costs lower than conventional distributed Hungarian methods, while maintaining superior formation integrity during transformation in cluttered environments.