Static and Dynamic Accuracy and Occlusion Robustness of SteamVR Tracking 2.0 in Multi-Base Station Setups

Lara Kuhlmann de Canaviri, Katharina Meiszl, Vana Hussein, Pegah Abbassi, Seyedeh Delaram Mirraziroudsari, Laurin Hake, Tobias Potthast, Fabian Ratert, Tessa Schulten, Marc Silberbach, Yannik Warnecke, Daniel Wiswede, Witold Schiprowski, Daniel Heß, Raphael Brüngel, Christoph M. Friedrich*

*Corresponding author for this work
16 Citations (Scopus)

Abstract

The tracking of objects and person position, orientation, and movement is relevant for various medical use cases, e.g., practical training of medical staff or patient rehabilitation. However, these demand high tracking accuracy and occlusion robustness. Expensive professional tracking systems fulfill these demands, however, cost-efficient and potentially adequate alternatives can be found in the gaming industry, e.g., SteamVR Tracking. This work presents an evaluation of SteamVR Tracking in its latest version 2.0 in two experimental setups, involving two and four base stations. Tracking accuracy, both static and dynamic, and occlusion robustness are investigated using a VIVE Tracker (3.0). A dynamic analysis further compares three different velocities. An error evaluation is performed using a Universal Robots UR10 robotic arm as ground-truth system under nonlaboratory conditions. Results are presented using the Root Mean Square Error. For static experiments, tracking errors in the submillimeter and subdegree range are achieved by both setups. Dynamic experiments achieved errors in the submillimeter range as well, yet tracking accuracy suffers from increasing velocity. Four base stations enable generally higher accuracy and robustness, especially in the dynamic experiments. Both setups enable adequate accuracy for diverse medical use cases. However, use cases demanding very high accuracy should primarily rely on SteamVR Tracking 2.0 with four base stations.

Original languageEnglish
Article number725
JournalSensors
Volume23
Issue number2
ISSN1424-8220
DOIs
Publication statusPublished - 01.2023

Funding

FundersFunder number
University of Applied Sciences and Arts Dortmund

    Research Areas and Centers

    • Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

    DFG Research Classification Scheme

    • 1.22-05 Personality Psychology, Clinical and Medical Psychology, Methodology
    • 2.23-08 Human Cognitive and Systems Neuroscience

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