Multi-UCAV cooperative autonomous attack path planning method under uncertain environment

Path planning of the unmanned aerial vehicle(UAV) under the condition of uncertainty of environment remains a challenge because of many constraints. In this paper, a multiple unmanned combat aerial vehicle (multi-UCAV) cooperative autonomous attack path planning method under complex and uncertain environment is put forward. A general framework of multi-UCAV cooperative combat and autonomous attack is designed. Then, the relative movement situation of the UCAV formation is studied and the task assignment model for attacking multi-target is established. On this basis, an improved ant colony algorithm (ACA) is used to solve the corresponding optimal problem. By taking the three degrees of freedom model of UCAV as a core and considering various constraints such as aerodynamic characteristics, thrust variation, target projection area and threat area, an accurate cooperative autonomous attack path planning model for multi-UCAV is built and an improved rolling pseudospectral method(RPM) is applied to calculate the optimal trajectory from the current location to the launch acceptable region. Simulation results show that the proposed ACA and RPM can deal with the task assignment and path planning of multi-UCAV effectively, and they have higher precision and better real-time compared with some existed methods.