摘要
基于Messy遗传算法(Messy GA),设计了移动机器人的通用路径规划算法,其中的优化目标包括最短路径、一定的平滑度和最优安全距离.在算法中加入了优化算子及交叉率和变异率的自适应调整,加快了收敛速度.仿真结果验证了所提方法的有效性.根据能力风暴机器人(AS-R)的实际运行要求,修改算法以扩大路径与障碍物之间的间隔度,并提出采用平滑的方法来优化路径.以AS-R为平台进行了轨迹跟踪实验.实验结果表明算法在随机摆放障碍物和实验室环境下可以实现路径规划,并能够最终实现AS-R机器人的全局路径规划.
Based on Messy genetic algorithm（Messy GA）,a general path planning algorithm for mobile robots is designed in which the optimized objects include the shortest path,the fine smoothness and the optimal safety distance.Optimized operators and the adaptive adjustment of the crossover rates and mutation rates are added into the algorithm in order to improve the convergence rate.Simulation results verify the effciency of the proposed method.According to the practical operation requirements of ability storm robot（AS-R）,the algorithm is modified to increase the distance between path and obstacles,and a smoothing method is introduced to optimize the path.The trajectory tracking experiments are conducted with the AS-R robot as the platform.The experiment results show that the algorithm can plan the paths in lab environment with randomly placed obstacles,and can realize the global path planning for AS-R robot finally.
出处
《信息与控制》
CSCD
北大核心
2012年第2期202-209,共8页
Information and Control
基金
浙江省自然科学基金资助项目(Y1100378)
