UAV Swarm Task Assignment Method Based on Artificial Gorilla Troops Optimizer

When Unmanned Aerial Vehicle (UAV) swarm works together, how to reasonably assign multiple targets and tasks on the ground is a practical problem. To solve this problem, a task assignment method based on Artificial Gorilla Troops Optimizer (GTO) is proposed in this research. The proposed method establishes a Cooperative Multiple Task Assignment Problem (CMTAP) model taking the sum of distance cost and loss cost as the objective function. First, the initial task assignment scheme is obtained by adopting real number encoding method. Then, the objective function is substituted, and solved using GTO, where the scheme corresponding to the minimum value of the objective function is the final assignment solution. The experimental results show that the proposed method can generate an effective task assignment scheme. Moreover, compared with the assignment results by Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO) and Deth First Search (DFS), the proposed method has faster convergence speed, higher stability and less cost of task assignment.