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| Complex Environment Path Planning Based on an Improved Ant Colony Algorithm |
| YANG Junqi, LIU Feiyang, ZHANG Hongwei
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| School of Electrical Engineering and Automation, Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Henan Polytechnic University, Jiaozuo 454003, China |
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Abstract This paper proposes an improved ant colony algorithm to solve the problem of slow and poor convergence. First, a correction strategy is introduced, which includes two local correction methods to reduce invalid paths. Second, an adaptive pheromone updating mechanism is developed to distinguish and volatilize the initial pheromone from the pheromone released. For the pheromone released in each iteration, a change law of time-varying volatilization factor is designed to volatilize independently and obtain pheromone volatilization mechanism with adaptive volatilization intensity. Finally, the proposed algorithm is applied to mobile robot path planning. Compared with the existing improved ant colony algorithms, the results show that the improved algorithm is excellent in terms of effective time, average distance and shortest distance.
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Received: 07 December 2022
Published: 07 November 2024
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