Food sorting trajectory optimization based on improved NURBS and Delta parallel robots

ObjectiveReduce the running time and impact of Delta robot in food sorting trajectory, improve the efficiency and stability of Delta robot operation.MethodsBased on the analysis of the food sorting system (using Delta robots), a Delta robot food sorting trajectory optimization method was proposed, which combined NURBS algorithm, sparrow search algorithm and butterfly optimization algorithm. Optimizing the running trajectory of Delta robot for NURBS curve planning with the goal of minimizing running time and impact, combining sparrow search algorithm and butterfly optimization algorithm to solve the model, which realized the optimization of Delta robot sorting trajectory.ResultsThe proposed Delta robot sorting trajectory optimization method could balance running time and impact, reduce running time by more than 6.00% and running impact by more than 80.00%. The dynamic grasping success rate of the system was over 99.00%, which could meet the requirements of food sorting.ConclusionOptimizing NURBS curves through a combination of runtime and impact optimization can effectively improve the food sorting performance of Delta robots.