Eye-to-hand robotic tracking and grabbing based on binocular vision

Closed

Yi-Chun Du, Taryudi Taryudi, Ching-Tang Tsai, Ming-Shyan Wang

2021 Microsystem Technologies Vol. 27 Issue 4 Article Cited by 18 SDG 17SDG 9SDG 16 Quartile

Abstract

This paper aims to study eye-to-hand robotic tracking and grabbing based on binocular vision. Two cameras placed on different locations gave different three-dimensional coordinates of the object from a binocular vision. The robot then analyzed the dynamic vision acquired from the stereo cameras and tracked the object in three-dimensional space utilizing continuously adaptive mean shift (CAMSHIFT) algorithm. Afterward, inverse and forward kinematics were implemented to move the robotic arm to the appropriate position so that it can grab the object using the end effector. The inverse kinematics was analyzed by a geometric algorithm to reduce the computational burden. Consequently, the experimental results verified that the eye-to-hand system was able to track and grasp the target successfully. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Affiliations

Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan, Taiwan; Faculty of Engineering, Universitas Negeri Jakarta, Jakarta, Indonesia

Research at a Glance

Premium content — register to unlock

Research at a Glance

Register to unlock

Topics & SDG Alignment

Premium content — register to unlock

Topics & SDG Alignment

Register to unlock

Collaboration

Premium content — register to unlock

Collaboration

Register to unlock

Author Profile (Selected)

Premium content — register to unlock

Author Profile (Selected)

Register to unlock

References Overview

Premium content — register to unlock

References Overview

Register to unlock

Journal & Source

Premium content — register to unlock

Journal & Source

Register to unlock

Metadata & Integrity

Premium content — register to unlock

Metadata & Integrity

Register to unlock