Journal of Computer Applications ›› 2021, Vol. 41 ›› Issue (7): 2121-2127.DOI: 10.11772/j.issn.1001-9081.2020081239

Special Issue: 前沿与综合应用

• Frontier and comprehensive applications • Previous Articles     Next Articles

Two-dimensional mapping of swarm robot based on random walk

LU Guoqing, SUN Hao   

  1. School of Artificial Intelligence, Hebei University of Technology, Tianjin 300130, China
  • Received:2020-08-18 Revised:2020-12-29 Online:2021-07-10 Published:2021-01-22


陆国庆, 孙昊   

  1. 河北工业大学 人工智能与数据科学学院, 天津 300130
  • 通讯作者: 孙昊
  • 作者简介:陆国庆(1995-),男,山东临沂人,硕士研究生,主要研究方向:移动机器人、机器人声源定位;孙昊(1979-),男,天津人,副教授,博士,主要研究方向:智能康复机器人、声源定位。

Abstract: Robots need to quickly and accurately obtain environmental map information when exploring unknown environments autonomously. For the problems of efficient exploration and map construction of unknown environments, the random walk algorithm was applied to the exploration of swarm robots, which simulate Brownian motion and build maps of the searched area. Then, the Brownian motion algorithm was improved to avoid the robot to search a region repeatedly by setting the maximum rotation angle when the robot walks randomly, so that the robot was able to explore more areas in the same time and the search efficiency of the robot was improved. Finally, simulation experiments were carried out through a group of mobile robots equipped with lidar, the influences of maximum rotation angle increment, the number of robots and movement steps of robot on the search area were analyzed.

Key words: swarm robot, random walk, mapping, Brownian motion, mobile robot

摘要: 机器人在未知环境自主探索时,需要快速准确地获取环境地图信息。针对高效探索和未知环境的地图构建问题,将随机行走算法应用于群机器人的探索中,机器人模拟布朗运动,对搜索区域建图。然后,改进了布朗运动算法,通过设置机器人随机行走时的最大旋转角度,来避免机器人重复性地搜索一个区域,使机器人在相同时间内探索更多的区域,提高机器人的搜索效率。最后,通过搭载激光雷达的多个移动机器人进行了仿真实验,实验分析了最大转角增量、机器人数量以及机器人运动步数对搜索区域的影响。

关键词: 群机器人, 随机行走, 地图构建, 布朗运动, 移动机器人

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