Title: Ant colony optimisation algorithm-based multi-robot exploration

Authors: Benjie Xiao; Hongming Su; Yilu Zhao; Xiong Chen

Addresses: Intelligent Control Research Lab, Department of Electronic Engineering, Fudan University, Shanghai 200433, China ' Intelligent Control Research Lab, Department of Electronic Engineering, Fudan University, Shanghai 200433, China ' Intelligent Control Research Lab, Department of Electronic Engineering, Fudan University, Shanghai 200433, China ' Intelligent Control Research Lab, Department of Electronic Engineering, Fudan University, Shanghai 200433, China

Abstract: The key problem of multi-robot exploration in unknown environment is how to appropriately select targets for the robots. In this paper, we present a new method to guide multi-robot exploration. Ant colony optimisation (ACO) is introduced to find the optimal target assignment for the robots. A new cost function is designed which takes into account distance, target position and robot density. The simulation results demonstrated that the proposed method effectively solves the problem of optimal target assignment and exploration efficiency is much increased.

Keywords: multi-robot exporation; multiple robots; coordinated exploration; ant colony optimisation; ACO; optimal target assignment; robot navigation; simulation; robot coordination; cooperating robots.

DOI: 10.1504/IJMIC.2013.051932

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.1, pp.41 - 46

Available online: 05 Feb 2013 *

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