Integrated Multi-UAV Motion Planning Under Kinematic Constraints Based on Enhanced Conflict-Based Search - Li, Liya; Liu, Yucong; Qi, Guoyuan; Ahn, Choon Ki (IEEE robotics and automation letters, 2025)
Multi-uncrewed aerial vehicle (UAV) performing tasks in obstacle-intensive aerospace environments requires prior motion planning to mitigate real-time tracking and control challenges. However, conventional hierarchical motion planning often leads to secondary conflicts and other issues. In this letter, we address the multi-UAV motion planning problem by explicitly considering their unique kinematic constraints, as well as the collision avoidance and obstacle avoidance problems in complex environments. First, we propose an integrated enhanced conflict-based search (ECBS) framework that employs a front-end and back-end unified approach to generate final trajectories while avoiding secondary conflicts directly. Second, we couple segmented trajectories with low-level search nodes by incorporating trajectory states into the cost function. Receding horizon optimization (RHO) is used to generate continuous and smooth trajectories that satisfy the UAV kinematic constraints. In addition, methods for resolving continuous conflicts in discrete spaces are designed. Finally, simulation results demonstrate the validity of the proposed algorithm and the effectiveness of the generated trajectories.