Multi-AUV Static Target Search Based on Improved PSO

Abstract

In recent years, with the development of AUVs, AUVs have been more applied in military and civilian fields, and the cooperative operation of multiple AUVs has become one of the research hotspots by virtue of its high efficiency and strong robustness in performing tasks. For the problem that it is difficult to fully cover the regional static target search in limited time, Voronoi diagram and biological competition model are used to realize the reasonable allocation of multiple AUVs and search area, and convert the multiple AUV search into single AUV search to simplify the problem and improve the search efficiency. In the search path planning within the sub-region, for the problems that the traditional particle swarm algorithm is easy to fall into local extrema and not applicable to continuous space, an improved particle swarm algorithm is proposed, combining the discrete particle swarm idea and adjusting the algorithm parameter factors to adapt the discrete space while accelerating the jump out of local extrema and improving the probability of detecting the target and the environment. The simulation results show that compared with the pure random route and the standard particle swarm route, the detection probability of target and environment is improved by 54.3% and 7.7%, respectively, which proves its effectiveness.