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Sensors 2017, 17(1), 104; doi:10.3390/s17010104

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks

Centre for Precision Technologies, School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
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Academic Editor: Joonki Paik
Received: 1 November 2016 / Revised: 21 December 2016 / Accepted: 4 January 2017 / Published: 7 January 2017
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)

Abstract

The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot with an overall tracking error of 0.25 mm. Also, the effectiveness of CRCHT technique in saving up to 60% of the overall time required for image processing. View Full-Text
Keywords: Hough transform; visual tracking; eye-to-hand cameras; industrial robotic applications; pick-and-place; target colour selection Hough transform; visual tracking; eye-to-hand cameras; industrial robotic applications; pick-and-place; target colour selection
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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).

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MDPI and ACS Style

Alzarok, H.; Fletcher, S.; Longstaff, A.P. 3D Visual Tracking of an Articulated Robot in Precision Automated Tasks. Sensors 2017, 17, 104.

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