Task Sequence Optimization for 6-DOF Manipulator in Press Forming Process

Our research team is developing a 6-DOF manipulator that is adequate for the narrow workspace of press forming processes. This paper addresses the task sequence optimization methods for the manipulator to minimize the task-finishing time. First, a kinematic model of the manipulator is presented, and the anticipated times for moving among the task locations are computed. Then, a mathematical model of the task sequence optimization problem is presented, followed by a comparison of three meta-heuristic methods to solve the optimization problem: an ant colony system, simulated annealing, and a genetic algorithm. The simulation shows that the genetic algorithm is robust to the parameter settings and has the best performance in both minimizing the task-finishing time and the computing time compared to the other methods. Finally, the algorithms were implemented and validated through a simulation using Mathworks' Matlab and Coppelia Robotics' V-REP (virtual robot experimentation platform).