DocumentCode
246402
Title
An Approach for Coordinating of the Cooperative Mapping in a Self-Adaptive Formation System Based on a Modification of the Ant Colony Algorithm
Author
Oliveira, Janderson R. ; Calvo, Rodrigo ; Romero, Roseli A. F. ; Figueiredo, Mauricio
Author_Institution
Dept. of Comput. Sci., Univ. of Sao Paulo, Sao Carlos, Brazil
fYear
2014
fDate
18-23 Oct. 2014
Firstpage
13
Lastpage
18
Abstract
In this work, an approach for cooperative and distributed mapping in a self-adaptive formation system based on a modified version of the ant colony optimization algorithm is proposed. The strategy is distributed, decentralized, real time and it is applied to tasks in which formation characteristic is an essential requirement. The coordination system´s design is inspired by the biological mechanisms that define a social organization in collective systems, specifically, the ant colony system. Voronoi tessalation and Delaunay triangulation techniques are used to model the formation strategy. The approach is adaptable for scenarios with suffer changes in the structure of the environment. The performance of the system is evaluated using a simulator. Simulation results show that the cooperative mapping is efficient, the trials are performed considering an indoor environment. Besides results show that the proposed formation approach is able to rearrange spatially the robots as they navigate, changing the relative robot distances according to the spatial environment restrictions.
Keywords
ant colony optimisation; computational geometry; mobile robots; path planning; Delaunay triangulation techniques; Voronoi tessalation; ant colony algorithm modification; biological mechanisms; collective systems; cooperative mapping coordination; coordination system design; distributed mapping; relative robot distances; robot navigation; self-adaptive formation system; social organization; spatial environment restrictions; Biology; Collision avoidance; Computational modeling; Robot kinematics; Robot sensing systems; Topology; Cooperative mapping; ant colony algorithm; formation; self-adaptive system;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics: SBR-LARS Robotics Symposium and Robocontrol (SBR LARS Robocontrol), 2014 Joint Conference on
Conference_Location
Sao Carlos
Print_ISBN
978-1-4799-6710-0
Type
conf
DOI
10.1109/SBR.LARS.Robocontrol.2014.16
Filename
7024089
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