Low Frequency Multi-Robot Networking

被引:0
|
作者
Sadler, Brian M. [1 ]
Dagefu, Fikadu T. [1 ,2 ]
Twigg, Jeffrey N. [1 ]
Verma, Gunjan [1 ]
Spasojevic, Predrag
Kozick, Richard J. [3 ]
Kong, Justin [1 ]
机构
[1] DEVCOM Army Res Lab, Adelphi, MD 20783 USA
[2] Rutgers State Univ, Dept Elect & Comp Engn, Piscataway, NJ 08855 USA
[3] Bucknell Univ, Dept Elect & Comp Engn, Lewisburg, PA 17837 USA
来源
IEEE ACCESS | 2024年 / 12卷
关键词
low frequency propagation; autonomy; multi-robot networking; complex environments; geolocation; distributed beamforming; parasitic arrays; cognitive radio; NONORTHOGONAL MULTIPLE-ACCESS; BIOMIMETIC ANTENNA-ARRAY; QUASI-SYNCHRONOUS CDMA; AD-HOC NETWORKING; PATH-LOSS MODEL; ELECTRICALLY-SMALL; LOW-PROFILE; PROPAGATION MEASUREMENTS; DECOUPLING NETWORKS; WAVE-PROPAGATION;
D O I
10.1109/ACCESS.2024.3358280
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Autonomous teams of unmanned ground and air vehicles rely on networking and distributed processing to collaborate as they jointly localize, explore, map, and learn in sometimes difficult and adverse conditions. Co-designed intelligent wireless networks are needed for these autonomous mobile agents for applications including disaster response, logistics and transportation, supplementing cellular networks, and agricultural and environmental monitoring. In this paper we describe recent progress on wireless networking and distributed processing for autonomous systems using a low frequency portion of the electromagnetic spectrum, here defined as roughly 25 to 100 MHz with corresponding wavelengths of 3 to 12 meters. This research is motivated by the desire to support autonomous systems operating in dense and cluttered environments by harnessing low frequency propagation, where meters long wavelengths yield significantly reduced scattering and enhanced penetration of obstacles and structures. This differs considerably from higher frequency propagation, requiring different low frequency propagation models than those widely employed for other bands. Progress in use of low frequency for autonomous systems has resulted from combined advances in low frequency propagation modeling, networking, antennas and electromagnetics, geolocation, multi-antenna array distributed beamforming, and mobile collaborative processing. This article describes the breadth and the depth of interaction between areas, leading to new tools and methods, especially in physically complex indoor/outdoor, dense urban, and other challenging scenarios. We bring together key results, models, measurements, and experiments that describe the state of the art for new uses of low frequency spectrum for multi-agent autonomy.
引用
收藏
页码:21954 / 21984
页数:31
相关论文
共 50 条
  • [21] Multi-robot hunting behavior
    Belkhouche, F
    Belkhouche, B
    Rastgoufard, P
    [J]. INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOL 1-4, PROCEEDINGS, 2005, : 2299 - 2304
  • [22] Planning for Multi-robot Localization
    Pinheiro, Paulo
    Wainer, Jacques
    [J]. ADVANCES IN ARTIFICIAL INTELLIGENCE - SBIA 2010, 2010, 6404 : 183 - 192
  • [23] Coordinated multi-robot exploration
    Burgard, W
    Moors, M
    Stachniss, C
    Schneider, FE
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2005, 21 (03) : 376 - 386
  • [24] Heterogeneous Multi-Robot Routing
    Chopra, Smriti
    Egerstedt, Magnus
    [J]. 2014 AMERICAN CONTROL CONFERENCE (ACC), 2014, : 5390 - 5395
  • [25] Distributed multi-robot localization
    Roumeliotis, SI
    Bekey, GA
    [J]. DISTRIBUTED AUTONOMOUS ROBOTIC SYSTEMS, 2000, : 179 - 188
  • [26] A Survey on Multi-robot Systems
    Cai, Yifan
    Yang, Simon X.
    [J]. 2012 WORLD AUTOMATION CONGRESS (WAC), 2012,
  • [27] Multi-robot cognitive formations
    Sousa, Miguel
    Monteiro, Sergio
    Machado, Toni
    Erlhagen, Wolfram
    Bicho, Estela
    [J]. 2012 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2012, : 545 - 550
  • [28] Multi-Robot Adversarial Coverage
    Yehoshua, Roi
    Agmon, Noa
    [J]. ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, 285 : 1493 - 1501
  • [29] Dynamic multi-robot coordination
    Vail, D
    Veloso, M
    [J]. MULTI-ROBOT SYSTEMS: FROM SWARMS TO INTELLIGENT AUTOMATA, VOL II, 2003, : 87 - 98
  • [30] Multi-robot coalition formation
    Vig, Lovekesh
    Adams, Julie A.
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2006, 22 (04) : 637 - 649