A spatially structured genetic algorithm for multi-robot localization

被引:0
|
作者
Andrea Gasparri
Stefano Panzieri
Federica Pascucci
机构
[1] Università degli Studi Roma Tre,Dip. Informatica e Automazione
来源
关键词
Mobile robot; Localization; Genetic algorithms; Complex networks;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper the multi-robot localization problem is addressed. A new framework based on a spatially structured genetic algorithm is proposed. Collaboration among robots is considered and is limited to the exchange of sensor data. Additionally, the relative distance and orientation among robots are assumed to be available. The proposed framework (MR-SSGA) takes advantage of the cooperation so that the perceptual capability of each robot is extended. Cooperation can be set-up at any time when robots meet, it is fully decoupled and does not require robots to stop. Several simulations have been performed, either considering cooperation activated or not, in order to emphasize the effectiveness of the collaboration strategy.
引用
收藏
页码:31 / 40
页数:9
相关论文
共 50 条
  • [41] A bounded uncertainty approach to multi-robot localization
    Spletzer, JR
    Taylor, CJ
    IROS 2003: PROCEEDINGS OF THE 2003 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4, 2003, : 1258 - 1265
  • [42] A "thermodynamic" approach to multi-robot cooperative localization
    Elor, Yotam
    Bruckstein, Alfred M.
    THEORETICAL COMPUTER SCIENCE, 2012, 457 : 59 - 75
  • [43] Collaborative Multi-Robot Localization in Natural Terrain
    Wiktor, Adam
    Rock, Stephen
    2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2020, : 4529 - 4535
  • [44] A collaborative localization scheme for multi-robot formation
    Jiang, Rong-Xin
    Tian, Xiang
    Xie, Li
    Chen, Yao-Wu
    Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2010, 42 (01): : 152 - 157
  • [45] A Collaborative Multi-robot Localization Method without Robot Identification
    Ozkucur, Nezih Ergin
    Kurt, Baris
    Akin, H. Levent
    ROBOCUP 2008: ROBOT SOCCER WORLD CUP XII, 2009, 5399 : 189 - 199
  • [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] Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation
    龚建伟
    黄宛宁
    熊光明
    满益明
    Journal of Beijing Institute of Technology, 2007, (02) : 151 - 156
  • [48] Optimization of pulse pattern for a multi-robot sonar system using genetic algorithm
    Nyakoe, GN
    Ohki, M
    Tabuchi, S
    Ohkita, M
    DEVELOPMENTS IN APPLIED ARTIFICAIL INTELLIGENCE, PROCEEDINGS, 2002, 2358 : 179 - 189
  • [49] Optimal trajectory-planning based on genetic algorithm for multi-robot system
    Gan, Ya-Hui
    Dai, Xian-Zhong
    Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2010, 27 (09): : 1245 - 1252
  • [50] Immunity-based adaptive genetic algorithm for multi-robot cooperative exploration
    Ma, Xin
    Zhang, Qin
    Chen, Weidong
    Li, Yibin
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2007, 4682 : 605 - 616