Trajectory Synthesis and Optimization Design of an Unmanned Five-Bar Vegetable Factory Packing Machine Based on NSGA-II and Grey Relation Analysis

Abstract

To address the problems of the complex structure and single packing trajectory of a packing machine, a hybrid-driven, five-bar packing machine for same-point pickup and different points of release in unmanned plant factories was designed, and a GRA-C method based on grey correlation analysis and CRITIC weighting for the quadratic optimization of Pareto solutions was proposed. According to the agronomic requirements, the original track of the packing machine was designed. The trajectory synthesis of the packing mechanism was completed based on the NSGA-Ⅱ multi-objective optimization algorithm. To reduce the overall size of the five-bar mechanism and to ensure its good motion performance, an optimization model for trajectory synthesis was established, and the optimal solution was obtained via the quadratic optimization of the Pareto front solution. To further improve the motion performance of the mechanism, the angular displacement curve at the secondary trajectory points was fitted. Through a comparative analysis with the solutions of three special points in the Pareto front solution set, it was found that the standard deviation of the angular velocity and the standard deviation of the angular acceleration after the quadratic optimization were 26.07% and 24.42% lower than the average values of the other three groups of solutions, respectively. The final optimization results were used to design the vegetable packaging machine, and the trajectory was found to be in good agreement with the expected trajectory, with a root mean square error of only 0.74.