Research on trajectory planning method for food sorting robot based on machine vision and improved BOA

ObjectiveReduce the trajectory running time, energy consumption, and operational impact of parallel robots during the food sorting process.MethodsBased on the analysis of the Delta parallel robot food sorting system, an improved 4-3-3-4 interpolation method was proposed for trajectory optimization of the Delta parallel robot. Built a model to optimize the joint coefficients of the 4-3-3-4 interpolation polynomial with the goal of optimizing the running time, energy consumption, and impact. By improving the butterfly optimization algorithm, the optimal solution for the motion trajectory of the parallel robot was obtained and its superiority was verified.ResultsCompared with conventional methods, the proposed trajectory optimization method had better operational efficiency and control effects, with the more smoother of the planned trajectory. In actual sorting, the sorting error was less than 0.5 mm, the sorting success rate was 99.60%, and the average sorting time was 0.620 s.ConclusionOptimizing polynomial interpolation can effectively improve the efficiency and stability of trajectory planning for parallel robots.