论文部分内容阅读
针对移动机器人的路径规划问题,提出了一种基于多策略混合人工鱼群算法的路径规划方法(MH-AFSA).为了提高传统人工鱼群算法(AFSA)的收敛速度和全局搜索能力,引入多策略混合机制,利用加权平均距离策略,扩大了人工鱼的视野范围.采用对数函数作为步长的移动因子,克服了传统固定步长的缺陷.进一步利用高斯变异策略扩大了种群的多样性.通过经典函数优化和旅行商问题(TSP)测试了算法的性能.最后,建立移动机器人的环境模型,给出了基于多策略混合人工鱼群算法的移动机器人路径规划步骤.通过数值仿真说明了所提算法的优越性和有效性.
In order to solve the path planning problem of mobile robots, a multi-strategy hybrid artificial fish swarm algorithm based path planning (MH-AFSA) is proposed.In order to improve the convergence speed and global search ability of traditional artificial fish swarm algorithm (AFSA) Strategy mixing mechanism, the weighted average distance strategy was used to expand the field of vision of artificial fish.The logarithmic function was used as the moving factor of the step to overcome the shortcomings of the traditional fixed step size, and the diversity of the population was further enlarged by Gaussian mutation strategy. The performance of the algorithm is tested by the classical function optimization and Traveling Salesman Problem (TSP) .Finally, the environment model of mobile robot is established and the path planning steps of mobile robot based on hybrid multi-strategy hybrid artificial fish swarm algorithm are given. The superiority and effectiveness of the proposed algorithm.