Pose-estimation and reorientation of pistons for robotic bin-picking

Abstract

Purpose – Picking up pistons in arbitrary poses is an important step on car engine assembly line. The authors usually use vision system to estimate the pose of the pistons and then guide a stable grasp. However, a piston in some poses, e.g. the mouth of the piston faces forward, is hardly to be directly grasped by the gripper. Thus, we need to reorient the piston to achieve a desired pose, i.e. let its mouth face upward, for grasping. Design/methodology/approach – This paper aims to present a vision-based picking system that can grasp pistons in arbitrary poses. The whole picking process is divided into two stages. At localization stage, a hierarchical approach is proposed to estimate the piston’s pose from image which usually involves both heavy noise and edge distortions. At grasping stage, multi-step robotic manipulations are designed to enable the piston to follow a nominal trajectory to reach to the minimum of the distance between the piston’s center and the support plane. That is, under the design input, the piston would be pushed to achieve a desired orientation. Findings – A target piston in arbitrary poses would be picked from the conveyor belt by the gripper with the proposed method. Practical implications – The designed robotic bin-picking system using vision is an advantage in terms of flexibility in automobile manufacturing industry. Originality/value – The authors develop a methodology that uses a pneumatic gripper and 2D vision information for picking up multiple pistons in arbitrary poses. The rough pose of the parts are detected based on a hierarchical approach for detection of multiple ellipses in the environment that usually involve edge distortions. The pose uncertainties of the piston are eliminated by multi-step robotic manipulations.