Title: Target attraction-based ant colony algorithm for mobile robots in rescue missions

Authors: Xiaoyong Zhang; Jun Peng; Huosheng Hu; Kuo-Chi Lin; Jing Wang

Addresses: School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China. ' School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China. ' School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK. ' Department of Mechanical, Materials and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA. ' Department of Computer Engineering, Bethune-Cookman University, Daytona Beach, FL 32114, USA

Abstract: After an earthquake, the road conditions are usually unknown and hazardous, which poses a great challenge for mobile robots to plan paths and reach the goal position safely for rescue operations. This paper presents a target attraction-based ant colony (TAAC) algorithm for the dynamic path planning of mobile robots operated in rescue missions. The global information of the road map is deployed to establish a target attraction function so that the probability of selecting an optimal path to the goal node is improved and the probability of converging to a local minimum path is reduced. Simulation results show that the proposed TAAC algorithm has a better dynamic performance and a faster convergence speed, compared with the existing max-min ant system algorithm.

Keywords: target attraction; ant colony optimisation; ACO; dynamic path planning; robot rescue; mobile robots; rescue missions; rescue robots; robot path planning; robot navigation; earthquakes; emergency management; emergency response; simulation.

DOI: 10.1504/IJMIC.2012.048920

International Journal of Modelling, Identification and Control, 2012 Vol.17 No.2, pp.133 - 142

Published online: 17 Dec 2014 *

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