Assessing the 6-DoF Accuracy and Robustness of the HTC VIVE Ultimate ® Stand-Alone Inside-Out Motion Tracker: A Robot-Driven Evaluation

The HTC VIVE Ultimate Tracker®, using inside-out tracking with internal stereo cameras for 6 DoF tracking without external cameras, offers a cost-efficient and simple setup for motion tracking. Originally for the gaming and VR industry, we explored its application beyond VR, providing C++ and Python source code for data capturing without a VR headset. This is the first study to evaluate the tracker’s accuracy in various experimental scenarios, including robotic and natural human movements. To assess the robustness of the displacement tracking accuracy, we used a robotic arm for precise, repeatable motion. Using an optical motion capture system as a reference, we conducted tests under varying conditions: lighting, movement velocity, environmental changes from displacing objects and human movement in front of the trackers, and varying the range of motion. On average, the HTC VIVE Ultimate Tracker showed an accuracy of 4.98 mm ± 4 mm. In stark contrast, orientation accuracy was highly robust and consistent across all conditions, with a mean RMSE of 0.36° ±0.31°, and remained unaffected by the perturbations that degraded positional tracking. Key factors influencing accuracy were lighting and range of motion. Under optimal conditions—good lighting and a reduced range of motion—the accuracy and precision improved, resulting in a mean error of 2.59 mm with a standard deviation of ± 0.81 mm. We also used five trackers to record human whole-body movements in ecologically valid scenarios, demonstrating an approximate positional accuracy of 1 cm, validated through two distinct pick-and-place tasks. While less accurate and precise than traditional fixed-camera-based motion capture systems, the HTC VIVE Ultimate Tracker® is a compelling alternative for research due to its low cost, ease of use, and capacity to track human and object motion beyond the constraints of conventional VR or motion capture environments.