Every-Efficient Motion Planning for Dual-Armed Robot by PID Gain Optimization with Genetic Algorithm

The purpose of this paper is to propose an energy-efficient pick-and-place motion planning that a robot grabs a workpiece on a belt-conveyor and releases it to specified position for saving energy of a dual-arm robot. The motion is evaluated by the objective function that has the number overshooting, the time of overshooting, the time of termination and the consumption of energy for the total minimization problem. The robot arm is controlled by PID controller, and its optimal PDI gains are obtained by a Genetic Algorithm. We conducted the numerical simulation to verify that the consumption of energy using a dual-arm robot can be decreased compared with that of one arm. The proposed motion planning has been implemented into real world motion planning problem. A dual-armed robot named duAro released by Kawasaki Heavy Industries, is used to carry out the real implementations to test the proposed pick-and-place motion planning. The experimental results show the effectiveness of the dual-armed motions compared with the single-arm motions for energy efficiency.