Research on AGV path planning based on improved ant colony algorithm
T his paper proposes an improved ant colony algorithm to address the problems of slow con-vergence,poor search capability and the tendency to fall into local optimum solutions in the traditional ant colony algorithm for automated guided vehicle(AGV)path planning.The paper introduces an a-daptive heuristic function to increase the directionality of the ant colony search,improves the phero-mone update strategy to avoid falling into local optimal solutions,and dynamically adjusts the phero-mone volatility coefficient to decrease with the iteration period,so as to improve the search efficiency and accelerate the convergence speed of the algorithm.The simulation results show that the algorithm has better convergence and search ability compared with other algorithms in the same environment.
ant colony algorithmautomated guided vehicle(AGV)path planningadaptivephero-mone
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