Marco Antonio Rodriguez-Fernandez
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Marco Antonio Rodriguez-Fernandez has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jordi Calvo Sanz
Department of Science Health, TecnoCampus Mataró-Maresme (TCM) - Universitat Pompeu Fabra (UPF). Research Group on Evidence and Innovation in Physiotherapy (GREIF), Barcelona, Spain
1 shared publication - Josep Lopez-Xarbau
TecnoCampus, Universitat Pompeu Fabra (UPF), 08302 Mataro, Spain
1 shared publication - Juan José Garcia Tirado
Department of Science Health, TecnoCampus Mataró-Maresme (TCM) - Universitat Pompeu Fabra (UPF). Research Group on Evidence and Innovation in Physiotherapy (GREIF), Barcelona, Spain
1 shared publication - Marcos Faundez-Zanuy
Tecnocampus, Universitat Pompeu Fabra, Mataró, Spain
1 shared publication
Latest Publications
- Open Access
Robot-Driven Calibration and Accuracy Assessment of Meta Quest 3 Inside-Out Tracking Using a TECHMAN TM5-900 Collaborative Robot
We present a systematic evaluation of the positional and rotational tracking accuracy of the Meta Quest 3 mixed-reality headset using a TECHMAN TM5-900 collaborative robot (±0.05 mm repeatability) as a highly repeatable robot-driven reference. The headset was rigidly attached to the robot’s tool flange and subjected to single-axis translational motions (200 mm along X, Y, and Z) and rotational motions (Roll ± 65°, Pitch ± 85°, and Yaw ± 85°). Each test was repeated three times, and the resulting trajectories were averaged to improve statistical robustness. Both data sources were integrated into a single Python-based application running on the same computer. The headset streamed its data via UDP, while the robot, implemented as an ROS2 node, published its data to the same host. This configuration enabled simultaneous acquisition of both streams, ensuring temporal consistency without the need for offline interpolation. All comparisons were performed in a relative reference frame, thereby avoiding the need for absolute hand–eye calibration. Coordinate-frame alignment was achieved using Singular Value Decomposition (SVD)-based rigid-body Procrustes analysis. Over 2848 synchronized samples spanning 151.46 s, the Meta Quest 3 achieved a mean translational RMSE of 0.346 mm (3D RMSE = 0.621 mm) and a mean rotational RMSE of 0.143°, with Pearson correlation coefficients greater than 0.9999 on all axes. These results show sub-millimeter positional tracking and sub-degree rotational tracking under controlled conditions, supporting the potential of the Meta Quest 3 for precision-oriented mixed-reality applications in industrial and research settings.
Open AccessRobot-Driven Calibration and Accuracy Assessment of Meta Quest 3 Inside-Out Tracking Using a TECHMAN TM5-900 Collaborative Robot
We present a systematic evaluation of the positional and rotational tracking accuracy of the Meta Quest 3 mixed-reality headset using a TECHMAN TM5-900 collaborative robot (±0.05 mm repeatability) as a highly repeatable robot-driven reference. The headset was rigidly attached to the robot’s tool flange and subjected to single-axis translational motions (200 mm along X, Y, and Z) and rotational motions (Roll ± 65°, Pitch ± 85°, and Yaw ± 85°). Each test was repeated three times, and the resulting trajectories were averaged to improve statistical robustness. Both data sources were integrated into a single Python-based application running on the same computer. The headset streamed its data via UDP, while the robot, implemented as an ROS2 node, published its data to the same host. This configuration enabled simultaneous acquisition of both streams, ensuring temporal consistency without the need for offline interpolation. All comparisons were performed in a relative reference frame, thereby avoiding the need for absolute hand–eye calibration. Coordinate-frame alignment was achieved using Singular Value Decomposition (SVD)-based rigid-body Procrustes analysis. Over 2848 synchronized samples spanning 151.46 s, the Meta Quest 3 achieved a mean translational RMSE of 0.346 mm (3D RMSE = 0.621 mm) and a mean rotational RMSE of 0.143°, with Pearson correlation coefficients greater than 0.9999 on all axes. These results show sub-millimeter positional tracking and sub-degree rotational tracking under controlled conditions, supporting the potential of the Meta Quest 3 for precision-oriented mixed-reality applications in industrial and research settings.