Dynamic Ellipsoidal Potential Fields Based UAV Formation Fault-Tolerant Formation Transformation

In recent years, unmanned aerial vehicle (UAV) formations have been increasingly employed across a multitude of domains. However, the expansion of formation scale and the increase in operational lifespan invariably lead to a higher probability of system-wide failures, which in turn escalates the risk of intra-formation collisions, posing a grave threat to the safety of ground personnel and equipment. To address these challenges, this paper proposes a resilient fault-tolerant formation transformation method for UAV formations based on dynamic ellipsoid potential field (DEPF). The novelty of our approach lies in the construction of velocity-correlated ellipsoid potential field avoidance regions and the subsequent reconfiguration of the repulsive force distribution within these regions. These innovations not only enhance the fault tolerance during formation transformation but also adjust the repulsive force intensity, effectively mitigating the local optima issue commonly encountered in conventional artificial potential field (APF) methods. The efficacy of the proposed method is validated through extensive simulations, which reveal significant improvements in obstacle avoidance performance. Specifically, compared to conventional APF algorithms, the proposed algorithm demonstrates a 22.3% enhancement in avoidance performance for static obstacles and an 88.8% improvement for dynamic obstacles. These results underscore the algorithm's effectiveness in ensuring flight safety during fault-tolerant formation transformation.