Application of Improved Gray Wolf Algorithm in Trajectory Planning of Pallet Handling Robot
In order to improve the running stability of the pallet handling robot,an optimal trajectory planning method for robot acceleration based on the improved gray wolf algorithm is proposed.Aiming at the problems of local convergence and insufficient optimization performance of gray wolf algorithm,the Logistic-Tent chaotic map is introduced to optimize the initial population;the differential optimization algorithm is introduced to improve the global search ability;the elimination evolution mechanism is introduced to optimize the population structure and improve the optimization performance in all-round way.Compared with the standard gray wolf algorithm and the particle swarm algorithm,simulation results show that improved gray wolf algorithm has better convergence speed and algorithm accuracy in different types of test functions.In the application of the trajectory planning of the handling robot,after the optimization of the algorithm,the maximum joint angular acceleration of the robot is reduced by 44.11%,which greatly improves the running stability.
handling robottrajectory planningaccelerationgray wolf algorithm
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