Paper Info
Title
On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics
Abstract
This paper aims at building autonomous controllers for swarm robots, specifically aimed at enforcing a given shape formation, here a column formation. The proposed approach features two main characteristics. Firstly, a state-of-the-art evolutionary setting is used to achieve the on-board optimization of the controller, avoiding any simulator-based approach. Secondly, as the cost of physical experiments might be prohibitively high for plain evolutionary approaches, a data mining approach is achieved on the top of evolution, rule discovery is used to discover the most promising regions in the controller search space. The merits of the approach are experimentally validated using a 5 robot formation, showing that the hybrid evolutionary learning process outperforms evolution alone in terms of swarm speed and shape quality.
Year
DOI
Venue
2011
10.1109/WI-IAT.2011.143
IAT
Keywords
Field
DocType
swarm robotics,autonomous controller,shape formation,off-line rule discovery,state-of-the-art evolutionary setting,column formation,data mining approach,plain evolutionary approach,simulator-based approach,on-board evolutionary algorithm,robot formation,hybrid evolutionary learning process,mobile robots,multi agent systems,learning artificial intelligence,light emitting diode,evolutionary computation,diffusion maps,evolutionary algorithm
Data mining,Control theory,Swarm behaviour,Evolutionary robotics,Evolutionary algorithm,Computer science,Evolutionary computation,Artificial intelligence,Robot,Mobile robot,Swarm robotics
Conference
Citations 
PageRank 
References 
1
0.37
15
Authors
7
Name
Order
Citations
PageRank
Asuki Kouno1202.46
Jean-Marc Montanier2718.03
Shigeru Takano38220.39
Nicolas Bredeche426933.86
Marc Schoenauer52500350.82
Michèle Sebag61547138.94
Einoshin Suzuki785393.41