Next Article in Journal / Special Issue
Compressed Voxel-Based Mapping Using Unsupervised Learning
Previous Article in Journal / Special Issue
Augmented Reality Guidance with Multimodality Imaging Data and Depth-Perceived Interaction for Robot-Assisted Surgery
Article Menu

Export Article

Open AccessArticle
Robotics 2017, 6(3), 14; doi:10.3390/robotics6030014

Automated Assembly Using 3D and 2D Cameras

Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 31 March 2017 / Revised: 20 May 2017 / Accepted: 19 June 2017 / Published: 27 June 2017
(This article belongs to the Special Issue Robotics and 3D Vision)
View Full-Text   |   Download PDF [21136 KB, uploaded 28 June 2017]   |  

Abstract

2D and 3D computer vision systems are frequently being used in automated production to detect and determine the position of objects. Accuracy is important in the production industry, and computer vision systems require structured environments to function optimally. For 2D vision systems, a change in surfaces, lighting and viewpoint angles can reduce the accuracy of a method, maybe even to a degree that it will be erroneous, while for 3D vision systems, the accuracy mainly depends on the 3D laser sensors. Commercially available 3D cameras lack the precision found in high-grade 3D laser scanners, and are therefore not suited for accurate measurements in industrial use. In this paper, we show that it is possible to identify and locate objects using a combination of 2D and 3D cameras. A rough estimate of the object pose is first found using a commercially available 3D camera. Then, a robotic arm with an eye-in-hand 2D camera is used to determine the pose accurately. We show that this increases the accuracy to < 1 and < 1 . This was demonstrated in a real industrial assembly task where high accuracy is required. View Full-Text
Keywords: robotics; assembly; 3D vision; 2D vision robotics; assembly; 3D vision; 2D vision
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Kleppe, A.L.; Bjørkedal, A.; Larsen, K.; Egeland, O. Automated Assembly Using 3D and 2D Cameras. Robotics 2017, 6, 14.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Robotics EISSN 2218-6581 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top