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

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.