Title
A PSO-based multi-robot cooperation method for target searching in unknown environments
Abstract
In this paper, we study the problem of multi-robot target searching in unknown environments. For target searching, robots need an efficient method with respect to their limitations and characteristics of the workspace. Every robotic search algorithm has several constraints. Our goal is to propose a distributed algorithm based on Particle Swarm Optimization (PSO) for target searching which satisfies the before-mentioned constraints. This extension of PSO is named A-RPSO (Adaptive Robotic PSO). A-RPSO acts as the controlling mechanism for robots. It is similar to PSO with two modifications: firstly it takes into account obstacle avoidance, secondly A-RPSO has a mechanism to escape from local optima. Various experimental results obtained in a simulated environment, show that A-RPSO is able to outperform other state of-the-art techniques in target searching problems. The performance of A-RPSO is much more significant compared with other approaches in two distinctive states particularly: large environments and small number of robots.
Year
DOI
Venue
2016
10.1016/j.neucom.2015.11.007
Neurocomputing
Keywords
Field
DocType
search problem,mobile robot,obstacle avoidance,cooperation
Obstacle avoidance,Particle swarm optimization,Search algorithm,Local optimum,Distributed algorithm,Artificial intelligence,Search problem,Robot,Machine learning,Mathematics,Mobile robot
Journal
Volume
Issue
ISSN
177
C
0925-2312
Citations 
PageRank 
References 
14
0.68
31
Authors
3
Name
Order
Citations
PageRank
masoud dadgar1140.68
Shahram Jafari2194.31
Ali Hamzeh321429.47