Multi-UAV Safe Net Capture With a MRF-Based Coordinated Controller: Theory and Experiments

Capturing aerial intruders with multiple uncrewed aerial vehicles (UAVs) using a net is challenging, as it requires safe target tracking without damaging the net. This article presents a coordinated controller based on Markov random field (MRF) with identified parameters for safe multi-UAV net capture. First, energy functions derived from UAV dynamic states form the MRF-based control structure, enabling coordinated flight without assuming a fixed net shape. Next, a reference velocity is designed to track the intruder, and the control input is obtained by solving the MRF via mean-field approximation. Finally, Gaussian process regression (GPR) identifies the MRF energy function parameters to regulate inter-UAV distances and improve capture safety. An optimized training point selection strategy improves GPR parameter estimation accuracy. Simulations and real-world experiments, including comparisons with existing net capture strategies, confirm the effectiveness of the proposed controller and the GPR-based parameter identification with the training point selection strategy.