Sorting path optimization of parallel robot based on improved Genetic Algorithm

Abstract

Abstract In industrial production, parallel robot is often used for sorting, battery clamp is divided into two structures, the classification and sorting, for multi-target sorting problems. The motion path of end-effector is planned, the overall sorting path is planned, and the practical problem is transformed into a similar traveling salesman problem. The improved genetic algorithm is proposed to optimize the sorting time sequence, and the optimized path shortens 10.23% total distance on average compared with random sorting and 5.37% total distance compared with fixed longitudinal sorting. The shortening of the total distance can lead to higher sorting efficiency in sorting and increase productivity.