摘要
针对蚁群算法在机器人路径规划过程中出现的收敛速度慢的缺陷,提出了基于改进蚁群算法规划机器人全局路径,在栅格地图中划定优选区域,并建立新的初始信息素浓度设置模型,对各点初始信息素浓度进行差异化设置,避免寻优的盲目性,提高了算法的收敛速度。实验结果表明,改进后的蚁群算法的收敛速度明显加快,优于传统算法,表明了该算法的有效性。
Aiming at the shortcomings of ant colony algorithm in robot path planning,this paper proposes a global path planning method of robots based on improved ant colony algorithm.This method delineates the preferred region in the grid map and establishes a new initial pheromone concentration setting model,differentiating the initial pheromone concentration at each point to avoid the blindness of optimization and improving the convergence speed of the algorithm.The experimental results show that the improved ant colony algorithm has significantly higher convergence rate than the traditional algorithm,verifying the effectiveness of the algorithm.
作者
曹新亮
王智文
冯晶
查敏
王宇航
CAO Xin-liang;WANG Zhi-wen;FENG Jing;ZHA Min;WANG Yu-hang(School of Electrical and Information Engineering,Guangxi University of Science and Technology,Liuzhou 545006;School of Computer Science and Telecommunication Engineering,Guangxi University of Science and Technology,Liuzhou 545006;Guangxi Key Lab of Multi-source Information Mining&Security,Guangxi Normal University,Guilin 541004;School of Computer Science and Information Engineering,Guangxi Normal University,Guilin 541004,China)
出处
《计算机工程与科学》
CSCD
北大核心
2020年第3期564-570,共7页
Computer Engineering & Science
基金
国家自然科学基金(61962007,61462008,61751213,61866004)
广西自然科学基金重点项目(2018GXNSFDA294001,2018GXNSFDA281009)
广西自然科学基金(2018GXNSFAA294050,2017GXNSFAA198365)
广西教育厅科研项目(YB2014209)
广西多源信息挖掘与安全重点实验室开放性研究课题(MIMS19-04)
广西科技大学创新团队“图像处理与智能认知及应用”(gxkjdxcxtd201504)
2017年广西科技大学硕士研究生创新项目(GKYC2017)。
关键词
蚁群算法
机器人
路径规划
栅格地图
改进蚁群算法
ant colony algorithm
robot
path planning
grid map
improved ant colony algorithm
