Title
Autonomous task allocation by artificial evolution for robotic swarms in complex tasks
Abstract
Swarm robotics is a field in which multiple robots coordinate their collective behavior autonomously to accomplish a given task without any form of centralized control. In swarm robotics, task allocation refers to the behavior resulting in robots being dynamically distributed over different sub-tasks, which is often required for solving complex tasks. It has been well recognized that evolutionary robotics is a promising approach to the development of collective behaviors for robotic swarms. However, the artificial evolution often suffers from two issues—the bootstrapping problem and deception—especially when the underlying task is profoundly complex. In this study, we propose a two-step scheme consisting of task partitioning and autonomous task allocation to overcome these difficulties. We conduct computer simulation experiments where robotic swarms have to accomplish a complex collective foraging problem, and the results show that the proposed approach leads to perform more effectively than a conventional evolutionary robotics approach.
Year
DOI
Venue
2019
10.1007/s10015-018-0466-6
Artificial Life and Robotics
Keywords
DocType
Volume
Robotic swarm, Evolutionary robotics, Autonomous task allocation, Task partitioning
Journal
24
Issue
ISSN
Citations 
1
1614-7456
1
PageRank 
References 
Authors
0.36
22
4
Name
Order
Citations
PageRank
Yufei Wei121.06
Motoaki Hiraga222.41
Kazuhiro Ohkura39324.69
Zlatan Car4142.31