改进遗传算法优化移动机器人动态路径研究

路径规划是目前的一个研究热点,特别是移动机器人的动态环境路径规划可以折射到很多领域的应用中,提出了一种新的遗传算法变异策略,所提出的变异操作同步检测变异节点附近的自由节点,并通过适应度函数值的计算,择优取代变异节点,及时剔除不可行路径,使得算法收敛更高效迅速。以移动机器人动态环境路径规划为例进行计算,并与其它的3种方法进行对比,结果显示所提出方法收敛的精度更高,收敛时迭代的次数更少,验证了所提出方法的优越性。

Research in Improved Genetic Algorithm Optimization of Dynamic Path of Mobile Robot

The path planning is currently a hot topic of research, especially in the dynamic environment of mobile robot path planning can be refracted into many fields of application.A new genetic algorithm mutation strategy was presented.It was mutation operation of the proposed variation synchronous detection node offree node nearby, by calculating the fitness function value, preferred substitution of mutation node, timely culling of viable path, and making more efficient algorithm converges rapidly.An example of environment of mobile robot path planning was calculated and compared with the other three methods.The results show that the method proposed has higher convergence accuracy, less number of times of iterative which verified the superiority of this method.