Wojewoda, KK, Culmer, PR, Jackson, AE et al. (1 more author) (2016) Position Tracking of a Passive Rehabilitation Robot. In: 2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). The 6th Annual IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, 20-23 Jun 2016, Chengdu, China. Institute of Electrical and Electronics Engineers ISBN 978-1-5090-2733-0
Abstract
This paper presents a position tracking system for real-time position estimation of a passive rehabilitation robot. The table-top robot shall be used for upper limb rehabilitation by stroke patients. Accurate estimates of the robot's position are determined by fusing data from two sensors: a laser optical sensor and a webcam. The laser optical sensor is mounted underneath the robot and tracks the motion of the robot relative to the surface on which the robot is used. The webcam is positioned above the robot and mounted on a stand fixed to the surface. The webcam detects the robot's motion relative to a fixed absolute coordinate system and supplies data at a lower frequency than the optical sensor. A data fusion scheme is implemented and validated in experiments where markers are moving along circular and pentagram trajectories. After the fusion is completed, a Kalman filter is implemented to investigate if it can improve the accuracy of the fusion tracking system. The results demonstrate that the developed fusion position tracking system can reliably track the robot’s position with greater accuracy than would be possible with the webcam or the optical sensor tracking systems on their own.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | sensor fusion; Kalman filter.; passive rehabilitation; position tracking |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Jun 2016 10:51 |
Last Modified: | 18 Nov 2016 02:39 |
Published Version: | https://doi.org/10.1109/CYBER.2016.7574785 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/CYBER.2016.7574785 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101191 |