Garage AGV Path Planning and Simulation Based on Improved DWA
Aiming at the path planning and real-time obstacle avoidance of AGV in complex path environment of intelligent garage,an improved hybrid algorithm combining ant colony algorithm and dynamic window method is proposed.In the global planning,the adaptive adjustment of pheromone volatilization coefficient and the fusion of angle parameters are introduced to establish the garage direction pheromone matrix to increase the guidance ability of target points,expand the direction selectivity of ants.In the local planning,the improved DWA of the obstacle distance evaluation sub-function based on elliptic equation is designed.By extracting the global path node of the improved ant colony algorithm as the new path evaluation sub-function,and under the global path constrains,the optimality of dynamic planning is realized.The system simulation results show that the algorithm can reasonably cars deal with the dynamic and static obstacles,more in line with the requirements of dynamic programming under the influence of multiple environmental factors in the actual operation of AGV.
garage AGVant colonyDWAdynamic and static obstacle avoidancepath planningelliptic equation
NETL
NSTL
万方数据
