Automatic Control System for Reach-to-Grasp Movement of a 7-DOF Robotic Arm Using Object Pose Estimation with an RGB Camera

In this study, we develop an automatic control system to perform the reach-to-grasp movement of a 7-DOF (Degrees of Freedom) robotic arm that has the same DOFs as a human arm, and an end-effector with the same shape as a human hand. The 6-DOF pose of the object to be grasped is estimated in real time only from RGB images using a neural network based object pose estimation model. Based on this information, motion planning is performed to automatically control the reach-to-grasp movement of the robotic arm. In the evaluation experiment, the 7-DOF robotic arm performs reach-to-grasp movements for a household object in different poses using the developed control system. The results show that the control system developed in this study can automatically control the reach-to-grasp movement to an object in a certain arbitrary pose.