计算机与现代化

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一种改进的未知动态环境下机器人混合路径规划方法

  

  1. (1.河海大学物联网工程学院,江苏常州213022;

    2.江苏省“世界水谷”与水生态文明协同创新中心,江苏南京211100

  • 收稿日期:2015-12-14 出版日期:2016-04-14 发布日期:2018-09-30
  • 作者简介:曹清云(1991-),男,湖南岳阳人,河海大学物联网工程学院硕士研究生,研究方向:机器人路径规划; 倪建军(1978-),男,安徽黄山人,河海大学物联网工程学院/江苏省“世界水谷”与水生态文明协同创新中心教授,博士,研究方向:智能机器人,神经网络,模糊系统; 王康(1991-),男,江苏徐州人,硕士研究生,研究方向:机器人路径规划和SLAM; 吴榴迎(1991-),女,浙江桐庐人,硕士研究生,研究方向:机器人导航。
  • 基金资助:

    国家自然科学基金资助项目(61203365); 江苏省自然科学基金资助项目(BK2012149; 中央高校基本科研业务费专项基金资助项目(2015B20114; 江苏省研究生创新项目(KYLX15_0496

A Robot Hybrid Path Planning Algorithm Under Improved Unknown and Dynamic Environment

  1. (1. College of Internet of Things Engineering, Hohai University, Changzhou 213022, China;

    2. Jiangsu Provincial Collaborative Innovation Center of World Water Valley and Water Ecological Civilization, Nanjing 211100, China)

  • Received:2015-12-14 Online:2016-04-14 Published:2018-09-30

摘要:

动态未知环境下的机器人路径规划是机器人导航领域的重要课题之一,采用传统的方法求解并不理想。针对这个问题,提出一种改进的机器人混合路径规划方法。首先利用改进的文化基因算法规划出较优的全局路径,指引机器人沿着全局路径行走,然后根据传感器探测到的局部环境信息,利用Morphin算法进行局部路径实时规划,使机器人有效地躲避动态障碍物。仿真实验表明,该算法在未知动态路径规划中具有良好的效果。

 

 

关键词:

text-indent: 21pt">mso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">动态路径规划; mso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">文化基因算法; Morphinmso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">算法; mso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">混合; mso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">未知环境

Abstract:

Robot path planning under dynamic and unknown environment is one of important issues in mobile robot navigation, which is difficult to deal with by traditional methods. Aiming at this problem, an improved hybrid path planning algorithm is proposed. In the proposed approach, an improved Memetic algorithm is used to obtain an optimal global path at first, which is used to navigate the robot. And then a Morphin algorithm is used to plan an optimal local path based on the information sensed to avoid dynamic obstacles. The simulation experiments results show that the proposed algorithm is of good efficiency in the path planning task under dynamic and unknown environment.

 

Key words: dynamic path planning, Memetic algorithm, Morphin algorithm, hybrid, unknown environment

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