A*-Based Path Planning Algorithm for Swarm Robotics

被引:1
|
作者
Izhboldina, Valeriia [1 ]
Usina, Elizaveta [1 ]
Vatamaniuk, Irina [1 ]
机构
[1] Russian Acad Sci, St Petersburg Inst Informat & Automat, 39,14th Line, St Petersburg 199178, Russia
关键词
Swarm robotics; Path planning; Route map; Mobile robots; Group control;
D O I
10.1007/978-3-030-60337-3_11
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Currently path planning for a swarm of mobile robots is a relevant problem in the domain of robotics. Various approaches to its solution exist. One of such approaches comprises different methods of informed sampling, which boost the search process through direction of search frontier towards the target. This paper presents combination of such method with the simplified representation of the operational environment, specifically, cellular decomposition. The proposed method ensures transition of a robot swarm into the predefined formation in such manner, that during robot motion along the planned paths no collisions occurred. The experimentation was performed with groups of 5, 10, 15, 20, 25 and 30 robots in three different scenes. Upon experimentation it was revealed, that for a swarm of 30 robots in a complex scene the path computing time does not exceed 7 s.
引用
收藏
页码:107 / 115
页数:9
相关论文
共 50 条
  • [21] Path-planning research in radioactive environment based on particle swarm algorithm
    Liu, Yong-kuo
    Li, Meng-kun
    Xie, Chun-li
    Peng, Min-jun
    Xie, Fei
    PROGRESS IN NUCLEAR ENERGY, 2014, 74 : 184 - 192
  • [22] Path planning based on improved multi-objective particle swarm algorithm
    Duan, Yiqin
    Zhang, Yi
    Zhang, Bin
    Wang, Yusen
    PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020), 2020, : 1005 - 1009
  • [23] Path planning of unmanned vehicles based on adaptive particle swarm optimization algorithm
    Zhao, Jiale
    Deng, Chaoshuo
    Yu, Huanhuan
    Fei, Hansheng
    Li, Deshun
    COMPUTER COMMUNICATIONS, 2024, 216 : 112 - 129
  • [24] Path Planning of Mobile Robots Based on an Improved Particle Swarm Optimization Algorithm
    Yuan, Qingni
    Sun, Ruitong
    Du, Xiaoying
    PROCESSES, 2023, 11 (01)
  • [25] Application of Particle Swarm Optimization Algorithm Based on Cloud Model for Path Planning
    Wei, Liansuo
    Dai, Xuefeng
    2011 AASRI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRY APPLICATION (AASRI-AIIA 2011), VOL 2, 2011, : 68 - 71
  • [26] The Robot Path Planning Based on Ant Colony and Particle Swarm Fusion Algorithm
    Xu, Qi-Lei
    Cai, Man-Man
    Zhao, Lei-Hong
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 411 - 415
  • [27] Autonomous Underwater Vehicle Path Planning Based on Improved Salp Swarm Algorithm
    Guo, Xuan
    Zhao, Dongming
    Fan, Tingting
    Long, Fei
    Fang, Caihua
    Long, Yang
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2024, 12 (08)
  • [28] Path Planning for a UGV using Salp Swarm Algorithm
    AlShabi, Mohammad
    Ballous, Khlaled Awad
    Nassif, Ali Bou
    Bettayeb, Maamar
    Obaideen, Khaled
    Gadsden, S. Andrew
    AUTONOMOUS SYSTEMS:SENSORS, PROCESSING, AND SECURITY FOR GROUND, AIR, SEA, AND SPACE VEHICLES AND INFRASTRUCTURE 2024, 2024, 13052
  • [29] Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm
    Zhang Z.
    Fang Q.
    Song J.
    Zhang X.
    Zhu Z.
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2021, 39 (06): : 1222 - 1232
  • [30] Quantum planning for swarm robotics
    Chella, Antonio
    Gaglio, Salvatore
    Mannone, Maria
    Pilato, Giovanni
    Seidita, Valeria
    Vella, Filippo
    Zammuto, Salvatore
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2023, 161