Paper Info
Title
Multi-Robot Dynamic Formation Path Planning With Improved Polyclonal Artificial Immune Algorithm
Abstract
The paper presents a novel multi-robot dynamic formation path planning algorithm. A combination of leader-follower method and improved polyclonal artificial immune algorithm is used to derive the formation architecture. Multi-robot formation is maintained through controlling the distance and angle between the leader and followers. Formation-change and leader-change are used to avoid obstacles. Control graph theory is used to the smooth exchange between two different isomorphic formation shapes. When follower detects obstacles, leader temporarily changes till it successfully avoids obstacles. Robots reach the desired positions and avoid obstacles with improved polyclonal artificial immune algorithm. Artificial immune network has been widely used in obstacles avoidance with the strong searching ability and learning ability. Improved polyclonal artificial immune algorithm increases the diversity of antibodies. Extensive experiments show that the proposed algorithm effectively maintains the geometrical shape of formation, smoothly changes the geometrical shape from a triangle formation to a line formation and successfully avoids obstacles.
Year
DOI
Venue
2014
10.2316/Journal.201.2014.4.201-2615
CONTROL AND INTELLIGENT SYSTEMS
Keywords
Field
DocType
Multi-robot dynamic formation, path planning, polyclonal algorithm, leader-follower, control graph theory
Motion planning,Control engineering,Artificial intelligence,Robot,Artificial immune algorithm,Mathematics
Journal
Volume
Issue
ISSN
42
4
1480-1752
Citations 
PageRank 
References 
0
0.34
4
Authors
4
Name
Order
Citations
PageRank
Li-xia Deng162.66
Xin Ma28917.25
Jason Gu342174.77
Yibin Li422659.56