Communicating Multi-UAV System for Cooperative SLAM-based Exploration

被引:31
|
作者
Mahdoui, Nesrine [1 ]
Fremont, Vincent [2 ]
Natalizio, Enrico [3 ]
机构
[1] Univ Technol Compiegne, Sorbonne Univ, CNRS, UMR 7253, F-60200 Compiegne, France
[2] Ecole Cent Nantes, LS2N, CNRS, UMR 6004, Nantes, France
[3] Univ Lorraine, LORIA, CNRS, UMR 7503, Vandoeuvre Les Nancy, France
关键词
Coordinated multi-robot system; UAV; Autonomous exploration; Frontier-based exploration; SLAM; Inter-robot communications; SIMULTANEOUS LOCALIZATION;
D O I
10.1007/s10846-019-01062-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the context of multi-robot system and more generally for Technological System-of-Systems, this paper proposes a multi-UAV (Unmanned Aerial Vehicle) framework for SLAM-based cooperative exploration under limited communication bandwidth. The exploration strategy, based on RGB-D grid mapping and group leader decision making, uses a new utility function that takes into account each robot distance in the group from the unexplored set of targets, and allows to simultaneously explore the environment and to get a detailed grid map of specific areas in an optimized manner. Compared to state-of-the-art approaches, the main novelty is to exchange only the frontier points of the computed local grid map to reduce the shared data volume, and consequently the memory consumption. Moreover, communications constraints are taken into account within a SLAM-based multi-robot collective exploration. In that way, the proposed strategy is also designed to cope with communications drop-out or failures. The multi-UAV system is implemented into ROS and GAZEBO simulators on multiple computers provided with network facilities. Results show that the proposed cooperative exploration strategy minimizes the global exploration time by 25% for 2 UAVs and by 30% for 3 UAVs, while outperforming state-of-the-art exploration strategies based on both random and closest frontiers, and minimizing the average travelled distance by each UAV by 55% for 2 UAVs and by 62% for 3 UAVs. Furthermore, the system performance is also evaluated in a realistic test-bed comprising an infrastructure-less network, which is used to support limited communications. The results of the test-bed show that the proposed exploration strategy uses 10 times less data than a strategy that makes the robots exchanging their whole local maps.
引用
收藏
页码:325 / 343
页数:19
相关论文
共 50 条
  • [1] Communicating Multi-UAV System for Cooperative SLAM-based Exploration
    Nesrine Mahdoui
    Vincent Frémont
    Enrico Natalizio
    Journal of Intelligent & Robotic Systems, 2020, 98 : 325 - 343
  • [2] Multi-UAV cooperative surveillance based on role switch strategy
    Zhu Q.
    Xu N.
    Huang B.
    Li Q.
    Zhou R.
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2021, 47 (05): : 928 - 938
  • [3] A Multi-UAV Collaborative SLAM Method Oriented to Data Sharing
    Shi D.-X.
    Yang Z.-Y.
    Jin S.-C.
    Zhang Y.-J.
    Su X.-D.
    Li R.-H.
    Jisuanji Xuebao/Chinese Journal of Computers, 2021, 44 (05): : 983 - 998
  • [4] A Cooperative Task Assignment Method of Multi-UAV Based on Self Organizing Map
    Zhu, Shurong
    Zhang, Yingzhou
    Gao, Yang
    Wu, Fan
    2018 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC 2018), 2018, : 437 - 442
  • [5] Monocular Visual SLAM Based on a Cooperative UAV-Target System
    Trujillo, Juan-Carlos
    Munguia, Rodrigo
    Urzua, Sarquis
    Guerra, Edmundo
    Grau, Antoni
    SENSORS, 2020, 20 (12) : 1 - 32
  • [6] Target Cooperative Location Method of Multi-UAV Based on Pseudo Range Measurement
    Qu Y.
    Zhang F.
    Gu R.
    Yuan D.
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2019, 37 (02): : 266 - 272
  • [7] Threat modeling of a multi-UAV system
    Almulhem, Ahmad
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2020, 142 : 290 - 295
  • [8] Multi-UAV Cooperative Multi-Target Allocation Method based on Differential Evolutionary Algorithm
    Song, Yuanjie
    Xi, Qingbiao
    Xing, Xiaojun
    Yang, Bing
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 1655 - 1660
  • [9] Cooperative Multi-UAV Collision Avoidance Based on Distributed Dynamic Optimization and Causal Analysis
    Lao, Mingrui
    Tang, Jun
    APPLIED SCIENCES-BASEL, 2017, 7 (01):
  • [10] A Path Planning Method for Multi-UAV System
    Marro, Alessandro Assi
    Garcia Goncalves, Luiz Marcos
    2013 IEEE LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS 2013), 2013, : 129 - 135