A Method to Make a Robot Understand What was a Target Object in Motion Copying System

Abstract

This paper presents a novel method to identify a target object based on position and force data during motion demonstration. MCS is a system that copy and reproduce a skillful human motion through bilateral teleoperation. Even though, MSC can teach a robot how to move, a robot cannot recognize a target object because conventional MCS does not record environmental information. In proposed system, a camera is used to add environmental information. We use object detection algorithm to detect not a target object but a robot itself. The detected robot area is used to combine manipulator's information in image space and in robotic work space. By checking detected robot area and haptic information, we can obtain a region around a target object automatically. After automatic target image data collection, we train Convolutional Auto Encoder(CAE) so that CAE can extract target information. The proposed neural network can selectively detect the target object for MCS, which means a robot understand a target for MCS. The results of end effectors' detection and target object extraction are shown in images through experiments.