Paper Info
Title
Co-evolution framework of swarm self-assembly robots.
Abstract
In this paper, we present a co-evolution framework of configuration and control for swarm self-assembly robots, Sambots, in changing environments. The framework can generate different patterns composed of a set of Sambot robots to adapt to the uncertainties in complex environments. Sambot robots are able to autonomously aggregate and disaggregate into a multi-robot organism. To obtain the optimal pattern for the organism, the configuration and control of locomoting co-evolve by means of genetic programming. To finish self-adaptive tasks, we imply a unified locomotion control model based on Central Pattern Generators (CPGs). In addition, taking modular assembly modes into consideration, a mixed genotype is used, which encodes the configuration and control. Specialized genetic operators are designed to maintain the evolution in the simulation environment. By using an orderly method of evaluation, we can select some resulting patterns of better performance. Simulation experiments demonstrate that the proposed system is effective and robust in simultaneously constructing the adaptive structure and locomotion pattern. The algorithmic research and application analysis bring about deeper insight into swarm intelligence and evolutionary robotics.
Year
DOI
Venue
2015
10.1016/j.neucom.2012.10.047
Neurocomputing
Keywords
Field
DocType
Co-evolution,Swarm robot,Genetic programming
Evolutionary robotics,Swarm behaviour,Swarm intelligence,Ant robotics,Genetic programming,Artificial intelligence,Modular design,Robot,Mathematics,Machine learning,Swarm robotics
Journal
Volume
ISSN
Citations 
148
0925-2312
2
PageRank 
References 
Authors
0.38
16
4
Name
Order
Citations
PageRank
Haiyuan Li1142.36
Hongxing Wei210122.41
Jiang-Yang Xiao330.73
Tianmiao Wang432268.45