HoloLens is one of the rare AR headsets that work and is been used by several people out there which is not as much as the smartphone user base but for an AR headset its big enough. HoloLens 2 which is a successor to the Microsoft’s former AR headset HoloLens launched back in 2019 and was quite a hit among the industrial users and even became available to normal consumers some months ago for $3500 but it was missing a major feature of the original HoloLens, the research mode.
The research mode basically uses a bunch of sensors on the HoloLens for research purposes by academic or industrial researchers to create an augmented reality environment that is not meant for deployment such as tracking obstacles and presenting objects in a mixed reality space.
The research mode on HoloLens 2 borrows all the previous research mode functionalities of the original HoloLens and adds a few more which comes with the new set of sensors on the later one mentioned below
- Accelerometer – used by the system to determine linear acceleration along the X, Y, and Z axes and gravity.
- Gyro – used by the system to determine rotations.
- Magnetometer – used by the system to estimate absolute orientation.
The research mode feature set of the former HoloLens
- Visible Light Environment Tracking Cameras – used by the system for head tracking and map building.
- Depth Camera – operates in two modes:
- Short-throw, high-frequency (30 FPS) near-depth sensing used for Hand Tracking
- Long-throw, low-frequency (1-5 FPS) far-depth sensing used by Spatial Mapping
- Two versions of the IR-reflectivity stream – used by the HoloLens to compute depth. These images are illuminated by infrared and unaffected by ambient visible light.
The new improved research mode on HoloLens 2 provides new functionalities such as hand-tracking and eye-tracking which can be accessed through APIs during the research mode helping to make experiments much interactive and useful. Apart from this, the new research mode also lets you access built-in computer vision algorithms such as SLAM (simultaneous localization and mapping) and spatial-mapping algorithm to create a better-mixed reality environment.
According to Microsoft, the new research mode can be proved quite useful in the field of robotics.