Paper Info
Title
Experimental studies on chemical concentration map building by a multi-robot system using bio-inspired algorithms
Abstract
In this article we describe implementations of various bio-inspired algorithms for obtaining the chemical gas concentration map of an environment filled with a contaminant. The experiments are performed using Khepera III and miniQ miniature mobile robots equipped with chemical gas sensors in an environment with ethanol gas. We implement and investigate the performance of decentralized and asynchronous particle swarm optimization (DAPSO), bacterial foraging optimization (BFO), and ant colony optimization (ACO) algorithms. Moreover, we implement sweeping (sequential search algorithm) as a base case for comparison with the implemented algorithms. During the experiments at each step the robots send their sensor readings and position data to a remote computer where the data is combined, filtered, and interpolated to form the chemical concentration map of the environment. The robots also exchange this information among each other and cooperate in the DAPSO and ACO algorithms. The performance of the implemented algorithms is compared in terms of the quality of the maps obtained and success of locating the target gas sources.
Year
DOI
Venue
2014
10.1007/s10458-012-9213-x
Autonomous Agents and Multi-Agent Systems
Keywords
Field
DocType
Particle Swarm Optimization,Mobile Robot,Particle Swarm Optimization Algorithm,Inertial Measurement Unit,Sensor Reading
Ant colony optimization algorithms,Particle swarm optimization,Asynchronous communication,Computer science,Interpolation,Algorithm,Inertial measurement unit,Artificial intelligence,Robot,Linear search,Machine learning,Mobile robot
Journal
Volume
Issue
ISSN
28
1
1387-2532
Citations 
PageRank 
References 
10
0.70
17
Authors
5
Name
Order
Citations
PageRank
Mirbek Turduev1104.75
Gonçalo Cabrita2293.49
Murat Kırtay3262.90
Veysel Gazi4525.28
Lino Marques540747.76