Task Cooperative Assignment for Heterogeneous Platforms Composed of UAV and USV

The autonomous assignment, negotiation and execution of a task for cross-domain heterogeneous unmanned platforms are hot topics in current research of unmanned systems. Aiming at the heterogeneous platform composed of the Unmanned Aerial Vehicle (UAV) and Unmanned Surface Vessel (USV), a task cooperative assignment method based on improved Discrete Particle Swarm Optimization (DPSO) is proposed. The idea of mutation and crossover in Genetic Algorithm (GA) is used to improve the DPSO to solve the mathematical model composed of optimization targets and constraints, which can quickly converge to the global optimal solution of the objective function. The idea of mutation and crossover can solve the problem that the DPSO is easy to fall into the local optimal solution, so that the algorithm can converge to the global optimal solution of the objective function. The simulation result shows that the method can complete assignment of tasks, autonomously and cooperatively, in the air-sea heterogeneous platforms.