Research on task allocation of multi-UAVs based on improved Particle Swarm Optimization algorithm

Abstract

Task allocation of multiple unmanned aerial vehicles (multi-UAVs) is a typical NP-hard problem. In this paper, according to practical battlefield needs, mathematical model is constructed based on complex constrains of task allocation, and objective function is constructed based on multi-UAVs’ global voyage and task time. An improved strategy of particle position based on basic Particle Swarm Optimization (PSO) algorithm is applied to the problem, and reasonable allocation schemes are obtained. The allocation schemes meet the complex constrains including task sequence, time window, UAVs’ capacities and flight path, and can be chosen and adjusted flexibly by the decision maker according to the practical battlefield needs. A large number of simulation experiments show that improved PSO algorithm is effective and provides a reference for multi-UAVs’ task allocation problem with complex constrains and multi-objectives.