Application of Multi-Task Parallel Control Technologies Enabling Autonomous Behavior Based on Robot's States to Picking Robot for Logistics

Abstract

Optimal control of robot is desired to automate complex tasks performed by humans. For example, a picking robot system is required to perform high-speed picking motion and grasp a variety of products. To achieve this, the arm and hand motions must be coordinated. However, since there are multiple controllers in the robotic system, it is difficult to deal with this problem only by coordinating them. In this study, we propose to apply the method of controlling multiple tasks in parallel according to the robot's states to the picking robot. The proposed method checks the execution status of tasks with multiple control modules and divides tasks according to their operation. Then it makes control requests at the appropriate time. We incorporated the proposed method into the picking robot system and measured the motion time. As a result, we confirmed that the grasping motion time was reduced by 0.53 seconds (24%) compared to the method without parallel control in the coordinated motion of the arm and hand.