Real-Time Corner Recognition, Robotic Tracking and Grasping of a Towel-like Object under Suspended Transportation

Abstract

This paper proposes a method for grasping a corner of a suspended and transporting towel-like object with a robot arm. In the past, manipulation of flexible objects has been performed when the towel-like object is in a static/quasi-static state or when the deformation of the object is predictable. However, there have been few studies on grasping under the condition that the toweling object is moving randomly. This study aims to enable grasping of a randomly moving towel-like object by introducing a cooperative vision system. As the cooperative vision system, we develop an environmental vision system using a stereo camera and a robot-mounted vision system using a camera and a laser with DOE (Diffractive Optical Element). Also, these vision systems operate cooperatively to recognize a state of the corner of a randomly moving towel-like object in real time. Moreover, we propose a method for tracking and grasping of the corner of the towel-like object using the information obtained by the vision systems. As a result, the grasp execution time in a series of operations was about 70% faster than in the previous study, and the expected value of execution time until success was halved.