A self-adaptive network for multi-robot warehouse communication

被引:0
作者
Ashwini Kumar Varma
Jyotirmoy Karjee
Debjani Mitra
Hemant Kumar Rath
Arpan Pal
机构
[1] Indian Institute of Technology (Indian School of Mines),Department of Electronics Engineering
[2] TCS Research & Innovation Lab,undefined
[3] TCS Research & Innovation Lab,undefined
[4] TCS Research & Innovation Lab,undefined
来源
Computing | 2021年 / 103卷
关键词
Self-adaptive network; Multi-robot system; Communication protocol; Prioritization; Optimal path selection; Outage probability; 68M10; 68M12; 65D19; 90B35;
D O I
暂无
中图分类号
学科分类号
摘要
With the growing popularity of e-commerce, warehouse communication needs to operate in a dynamic environment with multiple robots in the system. Such multi-robot systems have many practical issues in reality. Among the major issues, end-to-end reliable communication is seen to take up prominence in literature. The current work introduces a novel self-adaptive network structure with two of its essential sub-blocks namely ‘Prioritization’ and ‘Optimal Path Selection’ as part of communication protocol for effective and reliable communication. For the first sub-block, we propose transmission deadline and information content based priority model which significantly improves critical packet transmission success rate and for the second sub-block, an optimal path selection method is proposed as a new path planning method which is capable of reducing the outage probability of the failed transmission. A typical configuration of warehouse has been simulated in Network Simulator-3 (NS-3) and real warehouse data has been used in analyzing the proposed functional blocks. A closed-form expression of outage probability is also analytically derived. Results are promising to apply them for dynamic multi-robot systems in general, and specifically for warehouse applications.
引用
收藏
页码:333 / 356
页数:23
相关论文
共 50 条
  • [41] Performance Evaluation of Multi-Hop Communication Based on a Mobile Multi-Robot System in a Subterranean Laneway
    Liu, Qing-Ling
    Oh, Duk-Hwan
    [J]. JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2012, 8 (03): : 471 - 482
  • [42] Dynamic control of multi-robot formation
    Li, YM
    Chen, X
    [J]. 2005 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS, 2005, : 352 - 357
  • [43] An analysis of coordination in multi-robot systems
    Farinelli, A
    Iocchi, L
    Nardi, D
    [J]. 2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS, 2003, : 1487 - 1492
  • [44] Adaptive Particle Swarm Optimization with Local Search for Multi-robot Multi-point Dynamic Aggregation
    Dai, Shihao
    Jia, Ya-Hui
    Chen, Wei-Neng
    Mei, Yi
    [J]. PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION, 2023, : 195 - 198
  • [45] DYNAMIC BIOINSPIRED NEURAL NETWORK FOR MULTI-ROBOT FORMATION CONTROL IN UNKNOWN ENVIRONMENTS
    Ni, Jianjun
    Yang, Xiaofang
    Chen, Junfeng
    Yang, Simon X.
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, 2015, 30 (03) : 256 - 266
  • [46] DISTRIBUTED CONTAINMENT CONTROL FOR MULTI-ROBOT SYSTEM BASED ON HAMILTON AND WAVELET NETWORK
    Shao, Nuan
    Guo, Zhijia
    [J]. MECHATRONIC SYSTEMS AND CONTROL, 2020, 48 (01): : 65 - 71
  • [47] On the robustness of a synchronized multi-robot system
    Sergey Bereg
    Andrew Brunner
    Luis-Evaristo Caraballo
    José-Miguel Díaz-Báñez
    Mario A. Lopez
    [J]. Journal of Combinatorial Optimization, 2020, 39 : 988 - 1016
  • [48] A Survey and Analysis of Multi-Robot Coordination
    Yan, Zhi
    Jouandeau, Nicolas
    Cherif, Arab Ali
    [J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2013, 10
  • [49] Cooperative multi-robot target tracking
    Jung, Boyoon
    Sukhatme, Gaurav S.
    [J]. DISTRIBUTED AUTONOMOUS ROBOTIC SYSTEMS 7, 2006, : 81 - +
  • [50] A Survey of Multi-Robot Cooperation and Control
    Li, Ting
    [J]. PROCEEDINGS OF 2010 ASIA-PACIFIC YOUTH CONFERENCE ON COMMUNICATION, VOLS 1 AND 2, 2010, : 509 - 513