Multi-UCAV Cooperative Path Planning Using Improved Coevolutionary Multi-Ant-Colony Algorithm

摘要

Teams of unmanned combat aerial vehicles (UCAVs) are well suited to perform cooperative mission in hostile environment, and cooperative path planning holds great attention for improving the efficiency of multi-UCAV combating. In this paper, a mathematical formulation for cooperative path planning problem is presented based on the analysis of typical constraints in the scenario. Different from previous studies, the formulation introduces cooperation coefficient to estimate how the UCAV flight paths fulfill the cooperative constraints. Then a coevolutionary multi-ant-colony algorithm is designed and implemented to solve the above-mentioned problem, based on multi-ant-colony algorithm and coevolutionary strategy. The state transition rule and pheromone updating strategy is modified to increase the algorithm performance. Finally, the proposed method is validated to be effective and feasible to solve the cooperative constraints efficiently, and is effective for the multi-UCAV cooperative path planning problem.