A Hybrid Approach of Path Planning for Mobile Robots Based on the Combination of ACO and APF Algorithms

This paper presents an optimal method based on combination of artificial potential field (APF) and ant colony optimization (ACO) algorithms for global path planning of mobile robots working in partially known environments. Two steps constitute this approach. Firstly, free space model of mobile robot is established by using visible graph method and ACO algorithm is utilized in this model to search a global collision-free path which is the shortest routine through known static obstacles. Secondly, when unknown obstacles are encountered, APF algorithm is employed to generate a real-time local path so as to avoid collision. Results of simulation experiments show that the proposed approach has good performance in convergence speed, dynamic behavior and is fit for complex environment.

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