A comparative analysis of AR controller tracking technologies

Abstract

Augmented Reality (AR) and Virtual Reality (VR) controllers utilize a combination of different tracking technologies to determine spatial orientation and position. These tracking technologies include IR/LED tracking, IMU (inertial measurement unit) tracking, and VIO (visual-inertial odometry) tracking. The IR/LED system utilizes infrared sensors and LED constellations for precision tracking, the IMU system relies on accelerometers for responsive mobility, and the VIO system combines cameras and inertial measurements for a balanced solution in dynamic environments. These technologies play a critical role in enabling seamless interactions within virtual environments by providing real-time data on user movement.The most sophisticated AR/VR controllers utilize a combination of these three technologies. While utilizing all three technologies together maximizes controller tracking` performance, it also increases production costs while introducing constraints to the form and design of the controller. For controllers used with AR systems intended for enterprise use, it is hypothesized that controllers that feature all three tracking technologies may be over-engineered as enterprise use does not typically involve the dynamic movements required for consumer use such as gaming.This study presents findings from a series of user studies that evaluates the strengths and differences among these tracking technologies when performing different types of controller interactions. The user studies focused on quantitative user performance differences between controllers with different combinations of tracking technologies enabled as well as differences in user perception for performance and comfort. Among the key findings that will be presented are a breakdown of the types of interactions that rely on VIO tracking and how user performance and perception is affected by not having VIO tracking enabled.

Keywords: Augmented Reality, Virtual Reality, Mixed Reality, Controller Tracking, Inside-Out Tracking, Visual-Inertial Odometry

DOI: 10.54941/ahfe1004627