Enhanced location tracking in sensor fusion-assisted virtual reality micro-manipulation environments
Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. He...
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| Published in: | PloS one Vol. 16; no. 12; p. e0261933 |
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| Main Authors: | , , , |
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| Language: | English |
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Public Library of Science
28.12.2021
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios. |
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| AbstractList | Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios.Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios. Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios. |
| Audience | Academic |
| Author | Song, Cheol Prieto Prada, John David Im, Jintaek Oh, Hyondong |
| AuthorAffiliation | Boston University, UNITED STATES 1 Department of Robotics Engineering, DGIST, Daegu, South Korea 2 School of Mechanical, Aerospace and Nuclear Engineering, UNIST, Ulsan, South Korea |
| AuthorAffiliation_xml | – name: 1 Department of Robotics Engineering, DGIST, Daegu, South Korea – name: Boston University, UNITED STATES – name: 2 School of Mechanical, Aerospace and Nuclear Engineering, UNIST, Ulsan, South Korea |
| Author_xml | – sequence: 1 givenname: John David surname: Prieto Prada fullname: Prieto Prada, John David – sequence: 2 givenname: Jintaek surname: Im fullname: Im, Jintaek – sequence: 3 givenname: Hyondong surname: Oh fullname: Oh, Hyondong – sequence: 4 givenname: Cheol orcidid: 0000-0003-1909-9816 surname: Song fullname: Song, Cheol |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34962969$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1016/B0-12-227410-5/00414-2 10.1364/BOE.7.004816 10.1109/SVR51698.2020.00047 10.1109/ACC.1994.751905 10.1364/OL.41.004723 10.1371/journal.pone.0049473 10.1371/journal.pone.0173972 10.1109/TMECH.2004.828655 10.2196/12291 10.1371/journal.pone.0134501 10.1371/journal.pone.0092804 10.23919/EUSIPCO.2019.8902570 10.1089/109493103322278844 10.1002/lsm.20897 10.1364/BOE.410492 |
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| Copyright | COPYRIGHT 2021 Public Library of Science 2021 Prada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2021 Prada et al 2021 Prada et al |
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| Title | Enhanced location tracking in sensor fusion-assisted virtual reality micro-manipulation environments |
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| Volume | 16 |
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