Research on Robot Path Planning Based on Improved Adaptive Ant Colony Algorithm
Shao Xiao-Qiang, Zhichao Lv, Xuan Ke Zhao, Xinchao Nie · 2019
Aiming at the problem that ant colony algorithm is easy to fall into local optimal and slow convergence in robot path planning, a path planning method based on improved ant colony algorithm is proposed for static obstacle environment.This method improves the search efficiency of the algorithm by using the adaptive adjustment heuristic function; The attenuation coefficient is adjusted dynamically to accelerate the convergence speed of the algorithm based on ant colony rule, pheromone is updated and the maximum and minimum of pheromone concentration is limited.Simulation results show that compared with other algorithms in the same environment, the improved algorithm has a faster convergence rate when the path planning results are the same.The improved algorithm has obtained the optimal path in different complexity environments, which also shows the effectiveness and reliability of the algorithm.