【摘要】 提出一种基于传统蚁群算法改进的算法，将Dijkstra算法的搜索策略融入蚁群算法，用Dijkstra算法进行节点选取，使搜索导向性更加明确，并缩短收敛时间，再用蚁群算法进行优化，更新启发式函数，达到路径更短，弯折点更少。并在栅格建模环境中进行仿真实验，结果表明，融合后的算法收敛速度更快，弯折更少，并缩短了寻径距离，有效避免机器人进行盲目搜索，达到了全局最优的要求。更多还原

【Abstract】 An improved algorithm based on the traditional ant colony algorithm is proposed to integrate the search strategy of Dijkstra algorithm into the ant colony algorithm, node selection with Dijkstra algorithm to make the search orientation clearer and to shorten the convergence time, and then optimisation with the ant colony algorithm and updating of the heuristic function to achieve shorter paths and fewer bending points. And simulation experiments are carried out in the raster modelling environment, and the results show that the fused algorithm converges faster, with fewer bends, and shortens the path-seeking distance, which effectively avoids robots from conducting blind searches, and achieves the requirement of global optimum.更多还原