一种基于量子染色体变异的移动机器人路径规划融合算法

A Fusion Algorithm for Mobile Robot Path Planning Based on Quantum Chromosome Mutation

为了解决机器人路径规划中的"局部最小"问题,提出了一种基于量子染色体变异的人工势场法和栅格法相融合的移动机器人路径规划算法.首先,对人工势场的斥力场进行改进,然后利用融合的人工势场法和栅格法对路径进行规划,产生初始化种群,最后利用量子比特对染色体编码、利用量子染色体变异对种群个体进行更新,完成最佳路径搜索.仿真实验表明,本文提出的融合算法能够有效地避开障碍物,稳定地产生移动机器人的最佳规划路径,提高了种群质量和收敛速度,适合于求解复杂优化问题,达到了预期效果.

In order to solve the problem of local minima in mobile robot path planning,a fusion algorithm of artificial potential field and grid based on quantum chromosome mutation is proposed.Firstly,the repulsion field of artificial potential function is improved.Then,the fusion method of artificial potential field and grid is used to plan path for mobile robot and produce initializing population.Finally,quantum bit is used to code chromosome,and quantum chromosome mutation is used to update population individual for getting the best path.Simulation result shows that the proposed method can be used to avoid the obstacles effectively,get the optimal path for mobile robot stably and increase population quality and convergence rate.It is fit for the solution of complex optimization problems and achieves the desired results.