摘要
路径规划是移动机器人运动控制中的关键问题。针对传统蚁群算法在机器人全局路径规划中存在收敛速度慢、易陷入局部最优等缺点,提出一种改进型蚁群路径规划算法。首先,通过栅格法建立机器人运动环境模型,然后在传统蚁群算法基础上引入A*搜索算法的估价函数思想,改进蚁群算法的启发函数,增加目标节点与可选行进节点数对启发函数的影响。其次,在信息素更新公式中,通过引入Logistic增长函数对信息素挥发因子作自适应调整,提高算法速度与精度。最后,通过Matlab仿真实验证明,改进蚁群算法比传统算法在路径搜索速度和精度上都有较大提升。
Path planning is a key problem in motion control of mobile robot.An improved ant colony path planning algorithm is pro posed to solve the problems of slow convergence rate and getting stuck in the local optimum easily.First robot movement environment model is established by the grid method,and then on the basis of traditional ant colony algorithm,the evaluation function of A^*search algorithm is produced to improve ant colony algorithm function,increase the target node and optional node number's influence on the heuristic function.Secondly,in the update formula of pheromones,the speed and accuracy of the algorithm are improved by introduc ing logistic growth function to adjust the volatility factor of pheromones.Finally,through the Matlab simulation experiment,it is veri fied that the improved ant colony algorithm has greatly improved the speed and precision of the path search compared with the tradition al algorithm.
作者
颜杰
秦飞舟
翟帅华
YAN Jie;QIN Fei-zhou;ZHAI Shuai-hua(School of Physics and Electronic-Electrical Engineering,Ningxia University,Yinchuan 750021,China)
出处
《软件导刊》
2019年第2期5-8,共4页
Software Guide
基金
宁夏自然科学基金项目(NZ17261)
关键词
移动机器人
路径规划
改进蚁群算法
mobile robot
path planning
improved ant colony algorithm
