Head tracking using an optical soft tactile sensing surface
This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and...
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| Published in: | Frontiers in robotics and AI Vol. 11; p. 1410858 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Switzerland
Frontiers Media S.A
04-07-2024
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end-effector. The fibrescope was implemented to ensure the device's compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas-Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Püren Güler, Ericsson, Sweden Edited by: Benjamin Ward-Cherrier, University of Bristol, United Kingdom Reviewed by: Raza Qazi, University of Colorado Boulder, United States |
| ISSN: | 2296-9144 2296-9144 |
| DOI: | 10.3389/frobt.2024.1410858 |