Path planning of UUV based on HQPSO algorithm with considering the navigation error

Abstract

In the traditional path planning problem of Unmanned Underwater Vehicle (UUV), it is generally assumed that the navigation position information of UUV is accurate. However, the cumulative navigation position error caused by navigation system error of UUV cannot be ignored in practical applications. To get a safe path of UUV with considering navigation error, we propose the Hybrid Quantum-behaved Particle Swarm Optimization (HQPSO) algorithm to solve this problem. We improve the position and attitude error transfer model of UUV under integrated navigation, and give the mathematical models of collision avoidance constraints corresponding to regular obstacles and irregular obstacles respectively. At the same time, the terrain matching area and the terminal position error are used as constraints modification strategy of the HQPSO algorithm. Considering the influence of navigation error divergence rate and terrain matching aided navigation on path planning, two groups of comparative verification experiments are designed. The experimental results show that path planning method based on the HQPSO algorithm can effectively use the correction effect of terrain matching area on navigation error. This ensures that UUV can effectively avoid the adverse effects of navigation error, and get a path with the shortest navigation time. The method proposed in this paper shows strong engineering applicability.