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| Improved Adaptive Elite Ant Colony Algorithm for Robot Path Planning |
WANG
Ying1, WANG Xiaoru1, SUN Wanlong2, LIU Qi1
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| School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin City 132022, China |
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Abstract Aiming at the basic ant colony algorithm's problems of long path planning time, slow convergence speed, and high number of iterative stabilization in 2D grid maps for mobile robots, an improved adaptive elite ant colony algorithm is proposed. The algorithm improves the heuristic information function by introducing a distance parameter factor, selects the next node by using an adaptive pseudo-random state transfer rule, and also fuses the angle guidance factor into the transfer probability to reduce the search blindness, thus shortening the search time. In addition, an adaptive pheromone weight updating strategy is defined to reward the pheromone only for the optimal paths found in the contemporary search, which further improves the convergence speed. The ablation experiments, comparative experiments under different scales and environments show that the improved algorithm plans better paths and converges faster, verifying the superiority and feasibility of the algorithm.
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Published: 25 March 2024
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