A comprehensive review of the latest path planning developments for multi-robot formation systems

被引:19
作者
Abujabal, Nour [1 ]
Fareh, Raouf [2 ]
Sinan, Saif [3 ]
Baziyad, Mohammed [1 ]
Bettayeb, Maamar [2 ,4 ]
机构
[1] Univ Sharjah, Res Inst Sci & Engn RISE, Sharjah, U Arab Emirates
[2] Univ Sharjah, Elect Engn Dept, Sharjah, U Arab Emirates
[3] Ecole Technol Super ETS, Elect Engn Dept, Montreal, PQ, Canada
[4] King Abdulaziz Univ, CEIES, Jeddah, Saudi Arabia
关键词
path planning; multi-robot; formation control; leader-follower; virtual formation; behavior-based formation; dynamic formation; entralized decision; decentralized decision; distributed decision; hybrid decision; SURFACE VEHICLE FORMATIONS; LEADER-FOLLOWER FORMATION; MOBILE ROBOTS; ALGORITHMS; OPTIMIZATION; NAVIGATION; TRANSPORT; SELECTION; TEAM; UAVS;
D O I
10.1017/S0263574723000322
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
There has been a continuous interest in multi-robot formation systems in the last few years due to several significant advantages such as robustness, scalability, and efficiency. However, multi-robot formation systems suffer from well-known problems such as energy consumption, processing speed, and security. Therefore, developers are continuously researching for optimal solutions that can gather the benefits of multi-robot formation systems while overcoming the possible challenges. A backbone process required by any multi-robot system is path planning. Thus, path planning for multi-robot systems is a recent top research topic. However, the literature lacks a recent comprehensive review of path planning works designed for multi-robot systems. The aim of this review paper is to provide a comprehensive assessment and an insightful look into various path planning techniques developed in multi-robot formation systems, in addition to highlighting the basic problems involved in this field. This will allow the reader to discover the research gaps that must be solved for a better path planning experience for multi-robot formation systems. Finally, an illustrative comparative example is presented at the end of the paper to show the advantages and disadvantages of some popular path planning techniques.
引用
收藏
页码:2079 / 2104
页数:26
相关论文
共 145 条
[71]   Graph Neural Networks for Decentralized Multi-Robot Path Planning [J].
Li, Qingbiao ;
Gama, Fernando ;
Ribeiro, Alejandro ;
Prorok, Amanda .
2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, :11785-11792
[72]  
Lin CC, 2013, INT J INNOV COMPUT I, V9, P305
[73]   A dynamic priority based path planning for cooperation of multiple mobile robots in formation forming [J].
Liu, Shuang ;
Sun, Dong ;
Zhu, Changan .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2014, 30 (06) :589-596
[74]   Coordinated Motion Planning for Multiple Mobile Robots Along Designed Paths With Formation Requirement [J].
Liu, Shuang ;
Sun, Dong ;
Zhu, Changan .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2011, 16 (06) :1021-1031
[75]   A Dynamic Priority Strategy in Decentralized Motion Planning for Formation Forming of Multiple Mobile Robots [J].
Liu, Shuang ;
Sun, Dong ;
Zhu, Changan ;
Shang, Wen .
2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 2009, :3774-3779
[76]   A survey of formation control and motion planning of multiple unmanned vehicles [J].
Liu, Yuanchang ;
Bucknall, Richard .
ROBOTICA, 2018, 36 (07) :1019-1047
[77]   The angle guidance path planning algorithms for unmanned surface vehicle formations by using the fast marching method [J].
Liu, Yuanchang ;
Bucknall, Richard .
APPLIED OCEAN RESEARCH, 2016, 59 :327-344
[78]   Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment [J].
Liu, Yuanchang ;
Bucknall, Richard .
OCEAN ENGINEERING, 2015, 97 :126-144
[79]  
Luna R, 2011, IEEE INT C INT ROBOT, P3268, DOI 10.1109/IROS.2011.6048846
[80]  
Ma YC, 2013, CHIN CONTR CONF, P4915