Target attraction-based ant colony algorithm for mobile robots in rescue missions Online publication date:: Wed, 17-Dec-2014
by Xiaoyong Zhang; Jun Peng; Huosheng Hu; Kuo-Chi Lin; Jing Wang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 17, No. 2, 2012
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.
Online publication date:: Wed, 17-Dec-2014
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