This paper addressed a robot path planning algorithm based on improved ant colony optimization. The ant colony algorithm is used for a global path planning in robot rescue. A target attracting function is introduced to guide the searching process which can improve the search quality of ant colony algorithm in the complex and dynamic environment. The affectivity of proposed algorithm is verified in a standard test bed, RoboCupRescue simulation system.
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