Hand-eye calibration using a single image and robotic picking up using images lacking in contrast

Citations Over TimeTop 17% of 2020 papers

Abstract

This article proposes a hand-eye calibration using a new and easy method suitable for a camera mounted on the end-effector of an industrial robot using only a single image. The hand-eye calibration information could be used in robotic picking up of cubes using a monocular camera. Images captured from a particular pose of the camera have been segmented using a fusion of multiple methods such that the object information is obtained even in cases when there is less contrast between the object and the background, or in the presence of variation in lighting. The edge information, and subsequently the pose of the object was estimated using minimum number of images. In some of the cases a single image was sufficient but in case only a single edge edge is obtained, an additional image is grabbed after aligning the camera with the detected edge. An additional edge is estimated using a directional thresholding operation. The edge information in 3-D obtained using the calibration information was then used to calculate the pose of the object to facilitate robotic pick up. To ensure safety; a verification of the estimate was done using projection of the computed coordinates, and final pick up was done while monitoring the force to avoid damage due to collisions. The proposed approaches were physically implemented and experimentally validated.

Related Papers

• → A COMPARATIVE STUDY ON THRESHOLDING TECHNIQUES FOR GRAY IMAGE BINARIZATION(2017)11 cited
• → Multi-level thresholding and its application to feature extraction in machine parts(2005)1 cited
• → Global Thresholding and Multiple Pass Parsing(1997)47 cited
• → A localized thresholding method based on boundary detection(2004)