基于改进蚁群算法的移动机器人路径规划OA

Regarding the application of the traditional ant colony algorithm in robot path planning,there are limitations such as slow convergence,insufficient optimization search capability,and tendency to fall into local optima.An improved ant colony algo-rithm is proposed.To avoid the uncertainty of the ant colony's search direction at the initial moment,the initial pheromone concen-tration decreases with distance,which avoids low initial pheromones while improving search efficiency.The heuristic function is im-proved by introducing an adaptive adjustment factor to balance the convergence of the ant colony and its global search capability.The pheromone evaporation factor is dynamically adjusted to effectively overcome the low convergence efficiency and the tendency to get trapped in local optima inherent in traditional methods.Simulation results show that the improved algorithm has been validated in terms of both feasibility and effectiveness.