Research on Path Planning of Greenhouse Mobile Robot Based on Improved Ant Colony Algorithm
Addressing the challenges of long search times and slow efficiency in greenhouse mo-bile robot path planning,an improved ant colony algorithm-based approach is proposed.To bal-ance global search performance and convergence speed,an adaptive adjustment factor is intro-duced,building upon the heuristic function of the traditional ant colony algorithm.In the state transition probability formula,a stability factor is introduced to prevent premature entrapment in local optima.Additionally,a dynamic adjustment enhancement factor is introduced in the elite ant system,emphasizing edges likely to lead to optimal paths,thus achieving faster and more ac-curate convergence.Experimental results demonstrate that compared to the traditional ant colony algorithm,the improved algorithm significantly reduces the mean values of stable iteration count,optimal path length,and turning frequency,significantly enhancing the work efficiency of greenhouse mobile robots.
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