Position/Force Visual-Sensing-Based Robotic Sheet-Like Peg-in-Hole Assembly

Abstract

This article deals with a sheet-like peg-in-hole robotic assembly task which is usually done in manual operation. Thin-walled deformable objects will introduce some special uncertainties in robotic peg-in-hole assembly, which may make this kind of robotic assembly difficult. To deal with this issue, three four-phase selective compliance articulated robot arm (SCARA)-based peg-in-hole assembly strategies which imitate manual assembly with a hybrid switching force/position control scheme are proposed. Both position/force visual sensing methods are proposed based on a single-lens imaging system in an eye-to-hand configuration, respectively. Based on the developed visual sensing techniques, an iterative learning control (ILC) scheme is designed to approximate the synchronous position control between a SCARA robot and a two-degree of freedom (DoF) hybrid compliant gripper. The experiments are implemented on our built-up SCARA-based robotic peg-in-hole (peg: electrode ear, hole: plastic shell) assembly platform. The results indicate that the visual force sensing nonlinearity is about 3% at the full range, and the proposed robotic assembly strategies are suited to this kind of peg-in-hole assembly from industrial scenarios.