Research on trajectory planning method for Camellia oleifera fruit sorting robot based on multi-objective optimization
2023
FU Mingdi | LI Zhong | WANG Qianru | ZHAO Fei
<b>Objective:</b> Solved the problems of poor motion stability and accuracy in the food sorting process of parallel robots. <b>Methods:</b> Based on the analysis of the three degree of freedom food sorting robot system, a method proposed which combined polynomial interpolation and improve multi-objective particle swarm optimization algorithm for Delta robot trajectory optimization. As a parallel robot, the optimization of the shortest operation time, lowest energy consumption, and minimal motion impact were taken as multiple objectives. The improved multi-objective particle swarm optimization algorithm was applied to optimize the polynomial interpolation method, and its performance was validated. <b>Results:</b> The planning trajectory of the proposed planning method in the experiment was smoother and more efficient compared to conventional methods. In the actual selection of <i>Camellia oleifera</i> fruits, the accuracy was ＞99.00%, and the average screening time was 0.620 s. <b>Conclusion:</b> The trajectory planning optimization method proposed in the experiment has improved the sorting efficiency, accuracy, and stability of the <i>Camellia oleifera</i> fruit sorting robot.
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