Multi-Robot Cooperative Multi-Area Coverage Based on Circular Coding Genetic Algorithm

被引:2
作者
Xin, Bin [1 ,2 ]
Wang, Heng [1 ]
Li, Ming [3 ]
机构
[1] Beijing Inst Technol, Sch Automat, 5 South St, Beijing 100081, Peoples R China
[2] Key Lab Intelligent Control & Decis Complex Syst, 5 South St, Beijing 100081, Peoples R China
[3] BIT Nav & Control Technol Co Ltd, Beijing 102206, Peoples R China
关键词
cooperative area coverage; genetic algorithm; multiple robots; area allocation; TASK ALLOCATION; SYSTEMS; AREAS;
D O I
10.20965/jaciii.2023.p1183
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper studies the cooperative multi-area coverage problem with obstacles, which requires a group of robots to cover an area while avoiding collisions. This problem is very common in scenarios such as garbage removal, mine clearance, and regional information collection. The currently proposed algorithms usually have the problem of high redundancy and weak scene scalability. This paper designs a cooperative area coverage algorithm for multiple robots. First, a set of rules is proposed to divide the area to be covered into several small areas. Then, a genetic algorithm based on circular coding is designed to allocate these divided areas to several robots. Finally, the coverage path of the robot is designed using the zigzag method, so that the robot can cover the area allocated to it. Through computational experiments, it has been verified that this algorithm has efficiency advantages over state-ofthe-art algorithms in certain scenarios and has scalability for different scenarios.
引用
收藏
页码:1183 / 1191
页数:9
相关论文
共 50 条
  • [41] A survey on multi-robot coverage path planning for model reconstruction and mapping
    Almadhoun, Randa
    Taha, Tarek
    Seneviratne, Lakmal
    Zweiri, Yahya
    SN APPLIED SCIENCES, 2019, 1 (08):
  • [42] Multi-Robot Path Planning Based on the Developed RRT* Algorithm
    Li Yang
    Cu Rongxi
    Yang Chenguang
    Xu Demin
    2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 7049 - 7053
  • [43] An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm
    Chen, Lu
    Tan, Jie
    Wu, Tianci
    Tan, Zengxin
    Yuan, Guobo
    Yang, Yuhao
    Liu, Chiang
    Zhou, Haoyu
    Xie, Weisi
    Xiu, Yue
    Li, Gun
    MACHINES, 2024, 12 (11)
  • [44] Efficient Multi-Robot Cooperative Transportation Scheduling System
    Li, Xiaodong
    Lin, Yangfei
    Du, Zhaoyang
    Yin, Rui
    Wu, Celimuge
    2024 INTERNATIONAL CONFERENCE ON UBIQUITOUS COMMUNICATION, UCOM 2024, 2024, : 449 - 454
  • [45] Distributed Multi-agent Approach based on Priority Rules and Genetic Algorithm for Tasks Scheduling in Multi-robot Cells
    Maoudj, Abderraouf
    Bouzouia, Brahim
    Hentout, Abdelfetah
    Kouider, Ahmed
    Toumi, Redouane
    PROCEEDINGS OF THE IECON 2016 - 42ND ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2016, : 692 - 697
  • [46] Optimization of Multi-Robot Sumo Fight Simulation by a Genetic Algorithm to Identify Dominant Robot Capabilities
    Lehner, Joel Enrico
    Simi, Radovan
    Domberger, Rolf
    Hanne, Thomas
    2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2019, : 490 - 496
  • [47] Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithm
    Nazarahari, Milad
    Khanmirza, Esmaeel
    Doostie, Samira
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 115 : 106 - 120
  • [48] Economic Load Dispatch of A Multi-Area Power System Using Multi-Agent Distributed Optimization Based on Genetic Algorithm
    Fakhrmousavi, Seyed Yaser
    Mazafari, Seyed Babak
    Javadi, Shahram
    Aliabadi, Mahmood Hosseini
    ENERGY SCIENCE & ENGINEERING, 2025, : 1679 - 1690
  • [49] Cooperative Task Allocation for Multi-Robot Systems Based on Multi-Objective Ant Colony System
    Wang, Shengli
    Liu, Youjiang
    Qiu, Yongtao
    Zhang, Qi
    Huo, Feixiang
    Huangfu, Yafan
    Yang, Chun
    Zhou, Jie
    IEEE ACCESS, 2022, 10 : 56375 - 56387
  • [50] Multi-Robot Trajectory Tracking and Rendezvous Algorithm
    Patil, Amol
    Shah, Gautam
    IETE JOURNAL OF RESEARCH, 2022, 68 (06) : 4570 - 4576