摘要
目前移动机器人路径规划算法大多只考虑路程长度单一因素,所以出了一种多指标的综合评价启发函数,除考虑路径长度外将转向次数、环境高度两种因素加入启发函数中,引导蚂蚁沿着综合指标最优的路径行进。同时改进初始信息素分布且限制信息素范围,采用自适应挥发系数提升算法全局搜索性能,然后针对路径不平滑的问题,提出了三次B样条曲线对路径进行优化的方法。实验表明,改进算法获得的路径综合性能得到较大提升且更加平滑,因此更适合机器人实际工作。
At present,most of the path planning algorithms for mobile robots only consider the single factor of the distance length.Therefore,a multi index comprehensive evaluation heuristic function is proposed.In addition to considering the path length,the turning times and the environment height were added to the heuristic function to guide the ants to walk along the path with the optimal comprehensive index.At the same time,the initial pheromone distribution was improved and the pheromone range was limited.The adaptive volatility coefficient was used to improve the global search performance of the algorithm.Then,aiming at the problem of unsmooth path,a cubic B-spline curve was proposed to optimize the path.Experimental results show that the improved algorithm has a remarkable improvement in the path synthetic performance and the path is smoother,so it is more suitable for the actual work of robot.
作者
许伦辉
曾豫豪
XU Lun-hui;ZENG Yu-hao(School of Civil Engineering and Transportation,South China University of Technology,Guangzhou Guangdong 510640,China)
出处
《计算机仿真》
北大核心
2022年第7期407-411,共5页
Computer Simulation
关键词
蚁群算法
路径规划
移动机器人
Ant colony algorithm
Path planning
Mobile robot
作者简介
许伦辉(1965-),男(汉族),江西南康人,博士,教授,博士研究生导师,主要研究领域为智能交通、智能控制理论与应用;曾豫豪(1998-),男(汉族),江西赣州人,硕士研究生,主要研究领域为智能交通、路径规划。
