Flocking of partially-informed multi-agent systems avoiding obstacles with arbitrary shape

Verfasser / Beitragende:
[Jiaojie Li, Wei Zhang, Housheng Su, Yupu Yang]
Ort, Verlag, Jahr:
2015
Enthalten in:
Autonomous Agents and Multi-Agent Systems, 29/5(2015-09-01), 943-972
Format:
Artikel (online)
ID: 605514828
LEADER caa a22 4500
001 605514828
003 CHVBK
005 20210128100706.0
007 cr unu---uuuuu
008 210128e20150901xx s 000 0 eng
024 7 0 |a 10.1007/s10458-014-9272-2  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s10458-014-9272-2 
245 0 0 |a Flocking of partially-informed multi-agent systems avoiding obstacles with arbitrary shape  |h [Elektronische Daten]  |c [Jiaojie Li, Wei Zhang, Housheng Su, Yupu Yang] 
520 3 |a In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allowed, no matter if their boundary is smooth or non-smooth, and no matter it they are convex or non-convex. A novel geometry representation rule is proposed to transfer obstacles to a dense obstacle-agents lattice structure. Non-convex regions of the obstacles are detected and supplemented using a geometric rule. The uninformed agents can detect a section of the obstacles boundary using only a range position sensor. We prove that with the proposed protocol, uninformed agents which maintain a joint path with any informed agent can avoid obstacles that move uniformly and assemble around a point along with the informed agents. Eventually all the assembled agents reach consensus on their velocity. In the entire flocking process, no distinct pair of agents collide with each other, nor collide with obstacles. The assembled agents are guaranteed not to be lost in any non-convex region of the obstacles within a distance constraint. Numerical simulations demonstrate the flocking algorithm with obstacle avoidance both in 2D and 3D space. The situation when every agent is informed is considered as a special case. 
540 |a The Author(s), 2014 
690 7 |a Obstacle avoidance  |2 nationallicence 
690 7 |a Geometry representation  |2 nationallicence 
690 7 |a Flocking  |2 nationallicence 
690 7 |a Distributed control  |2 nationallicence 
690 7 |a Multi-agent system  |2 nationallicence 
700 1 |a Li  |D Jiaojie  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
700 1 |a Zhang  |D Wei  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
700 1 |a Su  |D Housheng  |u School of Automation, Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology), Ministry of Education, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Luoyu Road 1037, 430074, Wuhan, China  |4 aut 
700 1 |a Yang  |D Yupu  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
773 0 |t Autonomous Agents and Multi-Agent Systems  |d Springer US; http://www.springer-ny.com  |g 29/5(2015-09-01), 943-972  |x 1387-2532  |q 29:5<943  |1 2015  |2 29  |o 10458 
856 4 0 |u https://doi.org/10.1007/s10458-014-9272-2  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s10458-014-9272-2  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Li  |D Jiaojie  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zhang  |D Wei  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Su  |D Housheng  |u School of Automation, Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology), Ministry of Education, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Luoyu Road 1037, 430074, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Yang  |D Yupu  |u Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240, Shanghai, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Autonomous Agents and Multi-Agent Systems  |d Springer US; http://www.springer-ny.com  |g 29/5(2015-09-01), 943-972  |x 1387-2532  |q 29:5<943  |1 2015  |2 29  |o 10458