Cooperative Path Planning Method Based on Road Network Constraints for Vehicle-Mounted Multi-Rotor UAV Swarm

In order to solve the problems of multi-task point access in urban scenarios with constraints of the actual road network and diverse task duration, a cooperative path planning method based on ant colony algorithm (ACO) is proposed for vehicle-mounted multi-rotor UAV (unmanned aerial vehicle) swarm. Firstly, considering road network constraints, UAV performance parameters, task time and other constraints, the adjacency relationship between each task point and the road network is calculated in order to solve the optimal path of the UGV (unmanned ground vehicle). Then, the feasible path of the UGV is discretized in order to calculate the stopping point of the UGV and the task points sequence that can be accessed by each stopping point. Finally, the path planning of multi-UAV swarm accessing multi-task points is carried out for each stopping point. The real road network data is adopted for simulation experiments, the results show that the method can effectively plan the path of vehicle-mounted multi-rotor UAV swarm, achieve the shortest total time and coverage total task points.