Speed and Density Planning for a Speed-Constrained Robot Swarm Through a Virtual Tube

被引:0
作者
Song, Wenqi [1 ]
Gao, Yan [1 ,2 ]
Quan, Quan [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Tiangong Univ, Sch Control Sci & Engn, Tianjin 300387, Peoples R China
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2024年 / 9卷 / 11期
基金
中国国家自然科学基金;
关键词
Robots; Planning; Collision avoidance; Robot kinematics; Safety; Aerospace electronics; Vectors; Mobile robots; Decentralized control; Trajectory; Swarm robotics; constrained motion planning; motion control; virtual tubes; TRACKING;
D O I
10.1109/LRA.2024.3477094
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
The planning and control of a robot swarm in a complex environment has attracted increasing attention. To this end, the concept of virtual tubes has been taken up in our previous work. Specifically, a variable-width virtual tube is designed to prevent collisions with obstacles in complex environments. Based on the planned virtual tube for a large number of speed-constrained robots, the average forward speed and density along the virtual tube are further planned in this letter to improve safety and efficiency. In contrast to existing methods, the proposed method leverages global information and is well-suited for navigating confined spaces with speed-constrained robot swarms. Numerical simulations and experiments are conducted to show that the safety and efficiency of the passing-through process are improved.
引用
收藏
页码:10628 / 10635
页数:8
相关论文
共 24 条
  • [1] Ahn H., 2020, FORMATION CONTROL
  • [2] Biagiotti L., 2008, Trajectory Planning for Automatic Machines and Robots, DOI DOI 10.1007/978-3-540-85629-0
  • [3] Gao Y., 2024, IEEE Trans. Control Netw. Syst., DOI [10.1109/TCNS.2024.3463472, DOI 10.1109/TCNS.2024.3463472]
  • [4] Robust distributed control within a curve virtual tube for a robotic swarm under self-localization drift and precise relative navigation
    Gao, Yan
    Bai, Chenggang
    Quan, Quan
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2023, 33 (16) : 9489 - 9513
  • [5] Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability
    Luetzow, Laura
    Meng, Yue
    Armijos, Andres Chavez
    Fang, Chuchu
    [J]. 2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2023), 2023, : 7886 - 7893
  • [6] Online Trajectory Generation With Distributed Model Predictive Control for Multi-Robot Motion Planning
    Luis, Carlos E.
    Vukosavljev, Marijan
    Schoellig, Angela P.
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2020, 5 (02) : 604 - 611
  • [7] Optimal virtual tube planning and control for swarm robotics
    Mao, Pengda
    Fu, Rao
    Quan, Quan
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2024, 43 (05) : 602 - 627
  • [8] Mao PD, 2022, IEEE INT C INT ROBOT, P4498, DOI 10.1109/IROS47612.2022.9981842
  • [9] Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment
    McGuire, K. N.
    De Wagter, C.
    Tuyls, K.
    Kappen, H. J.
    de Croon, G. C. H. E.
    [J]. SCIENCE ROBOTICS, 2019, 4 (35)
  • [10] Olfati-Saber R, 2002, P AMER CONTR CONF, V1-6, P4690, DOI 10.1109/ACC.2002.1025398