Optimization Strategy for Object Picking and Placing on Table by Industrial Robot

Object sorting is a problem of separating objects of different kinds based on shape, size, or any other feature into separate stacks to process those separately. In the food processing industry, object sorting is used to separate fruits of different grades. Separating fruits into different grades is essential for quality control. Manual sorting is slower and costs more than automated sorting. This paper presents a novel solution for the object sorting problem using YOLOv8x and various optimization algorithms (ILP, GA and PSO). Here, the object sorting problem is solved by modelling it as a TSP. Through experiments, it was observed that a PSO-based approach could solve the object-sorting problem efficiently. The PSO method obtained a near-optimal solution with 42% less processing time than those obtained from the ILP method, which would enhance the productivity and performance of the industrial robot.