融合DWA和QPSO算法的USV动态局部路径规划算法

Dynamic Local Path Planning Algorithm for USA Combining DWA and QPSO Algorithm

针对无人水面艇(USV)在动态环境中的局部路径规划问题,传统的动态窗口法(DWA)把速度集合离散化处理求取最优速度,计算量大且速度分辨率对动态路径规划的影响大。基于此,论文提出了融合DWA和量子粒子群算法(QP-SO)的USV动态局部路径规划算法。首先论文在分析初始DWA的基础上,考虑国际海事规则和船舶机动性能等方面要求,建立融合避碰规则的动态窗口模型。然后在速度窗口中融入QPSO方法,将USV动态局部路径规划问题转化为多目标多约束优化问题。最后仿真验证了融合算法能够使USV在约束和规则下,获得最优的速度和航向,安全与目标船完成会遇,且运行效率更高。

Aiming at the local path planning problem of the unmanned surface vehicle(USV)in a dynamic environment,the traditional dynamic window approach(DWA)discretizes the speed set to obtain the optimal speed.The amount of calculation is large and the speed resolution has a large impact on the dynamic path planning.So,a dynamic local path planning algorithm for USA based on DWA and quantum particle swarm algorithm(QPSO)is proposed.Firstly,based on the analysis of the initial DWA,the paper considers the requirements of COLREGS and ship maneuverability,and establishes a dynamic window model that incorporates collision avoidance rules.Then the QPSO is incorporated into the velocity window to transform the dynamic local path planning problem into a multi-objective and multi-constraint optimization problem.Finally,the simulation verifies that the fusion algorithm can enable the USV to obtain the optimal speed and heading under constraints and rules,and can safely complete the encounter with the target ship,and it has a higher operating efficiency.