A Benchmark for Multi-Robot Planning in Realistic, Complex and Cluttered Environments

被引:1
|
作者
Schaefer, Simon [1 ]
Palinieri, Luigi [2 ]
Heuer, Lukas [2 ]
Dillmann, Ruediger [1 ]
Koenig, Sven [3 ]
Kleiner, Alexander [2 ]
机构
[1] KIT, Karlsruhe, Germany
[2] Robert Bosch GmbH, Corp Res, Stuttgart, Germany
[3] Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90007 USA
来源
2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2023) | 2023年
关键词
D O I
10.1109/ICRA48891.2023.10161005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Several successful approaches exist for solving the complex problem of multi-robot planning and coordination. Due to the lack of adequate benchmarking tools, comparing these approaches and judging their suitability for use in realistic scenarios is currently difficult. Therefore, we propose an open-source benchmark suite that aims to close this gap. Unlike existing benchmarks, our approach uses full-stack multi-robot navigation systems in realistic 3D simulated environments from the intralogistic and household domains. Using the open-source frameworks ROS 2, Gazebo and RMF allows the user to add other robot platforms easily. The framework provides easy-to-use abstractions, typical metrics and interfaces to several established planning libraries for multi-robot systems. With all these features, our framework successfully aids practitioners and researchers in comparing multi-robot planning and coordination systems to the state of the art. Our experiments show how the proposed benchmark simplifies gaining insights on relevant close to real-life robotics use cases.
引用
收藏
页码:9231 / 9237
页数:7
相关论文
共 50 条
  • [1] Reinforced Potential Field for Multi-Robot Motion Planning in Cluttered Environments
    Zhang, Dengyu
    Zhang, Xinyu
    Zhang, Zheng
    Zhu, Bo
    Zhang, Qingrui
    2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, IROS, 2023, : 699 - 704
  • [2] Global Planning for Multi-Robot Communication Networks in Complex Environments
    Kantaros, Yiannis
    Zavlanos, Michael M.
    IEEE TRANSACTIONS ON ROBOTICS, 2016, 32 (05) : 1045 - 1061
  • [3] Multi-Robot Patrolling with Coordinated Behaviours in Realistic Environments
    Iocchi, Luca
    Marchetti, Luca
    Nardi, Daniele
    2011 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 2011, : 2796 - 2801
  • [4] Multi-Robot Path Planning for Comprehensive Area Coverage in Complex Environments
    Kumar, Manish
    Ghosh, Arindam
    Ojha, Muneendra
    2024 28TH INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS, MMAR 2024, 2024, : 562 - 567
  • [5] Real-Time Multi-Robot Mission Planning in Cluttered Environment
    Lu, Zehui
    Zhou, Tianyu
    Mou, Shaoshuai
    ROBOTICS, 2024, 13 (03)
  • [6] Multi-Robot Mission Planning in Dynamic Semantic Environments
    Kalluraya, Samarth
    Pappas, George J.
    Kantaros, Yiannis
    2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA, 2023, : 1630 - 1637
  • [7] Multi-robot Coordination and Planning in Uncertain and Adversarial Environments
    Lifeng Zhou
    Pratap Tokekar
    Current Robotics Reports, 2021, 2 (2): : 147 - 157
  • [8] Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells
    Meng Zhou
    Zihao Wang
    Jing Wang
    Zhengcai Cao
    IEEE/CAAJournalofAutomaticaSinica, 2024, 11 (07) : 1643 - 1655
  • [9] Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells
    Zhou, Meng
    Wang, Zihao
    Wang, Jing
    Cao, Zhengcai
    IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2024, 11 (07) : 1643 - 1655
  • [10] Collaborative Multi-Robot Transportation in Obstacle-Cluttered Environments via Implicit Communication
    Bechlioulis, Charalampos P.
    Kyriakopoulos, Kostas J.
    FRONTIERS IN ROBOTICS AND AI, 2018, 5