Inside-Out tracking with LPSLAM and LPVR-DUO
LPSLAM can function as the optical tracking system for LPVR-DUO. To fully integrate it, the communication between the two systems must be configured, and a fiducial marker in the platform’s IMU must be set up to perform the IMU inter-calibration.
1) Varjo XR-3 camera adjustment
For better tracking performance with LPSLAM, it is recommended that the camera’s autoexposure be deactivated, and the Exposure and ISO values be set manually via Varjo Base. To allow the cameras to see inside the vehicle clearly:
Reduce the impact of brightness coming from outside the windows and prioritize indoor lighting by underexposing the image slightly.
Set a low ISO setting to reduce the sensor’s sensitivity to light and prevent bright areas, such as windows, from overexposing the image. If the lighting is very dim, you can increase the ISO. However, keep in mind that higher ISO settings may introduce noise into the image.
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2) Setting up a fiducial marker
First, choose a fiducial marker from the Chilitags library of pre-made markers (available here) and print it out. Attach the marker to the reference/platform IMU and ensure it’s placed in a location visible to the HMD cameras.
The choice of Chilitags marker does not matter, as long as it is the correct physical size for the configuration. However, keep in mind that the markers in the downloaded folder are already categorized as mini or big, and with or without borders. If you choose a marker with a border, ensure that it is printed with the border.
In your LPSLAM configuration file, set a tracker of type Marker
and configure the corresponding parameters. Adjust these parameters as needed to ensure quick detection of the fiducial marker while maintaining a stable tracked pose. For more information on the Marker tracker parameters, refer to the configuration file documentation.
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"trackers": [
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"type": "Marker",
"configuration": {
"marker_size": 0.045,
"process_noise": 0.8,
"observation_noise": 0.2,
"show_tags": true,
"detect_only": 90
}
]
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The detect_only
parameter is optional, but it is recommended to set it to the ID of the chosen fiducial marker. This helps prevent the tracker
from mistakenly identifying image features as markers that are not actually present in the scene or when using other fiducial markers to enhance feature-poor surfaces.
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3) Setting up communication in LPSLAM
For a faster and easier setup, the configs
folder has the pre-configured file lpvr-duo.json
to copy-paste the contents or upload it to the driver.
Proxy ports
LPSLAM generates two types of absolute 6DoF poses within the Visual-SLAM global reference frame:
Visual-SLAM poses: The estimated poses of the headset.
Marker poses: The estimated poses of the fiducial markers visible in the scene.
Each pose type is sent to a different proxy port, configured separately for each tracker
using the proxy_port
parameter, as shown below:
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"trackers": [
{
"type": "VSLAMStereo",
"configuration": {
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"proxy_port": 5002
}
},
{
"type": "Marker",
"configuration" : {
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"proxy_port": 5003
}
}
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Tracking IDs
Each tracked object has to have a tracking ID. For a tracker
of type VSLAMStereo
or VSLAMMono
, the tracked object is the system to which the camera is attached, in this case, the HMD. For the Marker
tracker, each fiducial marker in the scene represents a tracked object.
The tracking ID for
VSLAMStereo
orVSLAMMono
trackers is configured using thetracking_id
parameter.
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"trackers": [
{
"type": "VSLAMStereo",
"configuration": {
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"tracking_id": 1
}
},
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The tracking IDs for fiducial markers detected by the
Marker
tracker are directly defined by the markers chosen from Chilitags' library of pre-made tags, as each marker comes with a pre-defined ID. Therefore, if marker90
is chosen, the tracking ID will also be90
.
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4) Running LPSLAM + LPVR-DUO
After setting the fiducial marker and configuring the proxy ports and tracking ID, launch Varjo Base and let it run in the background. Then, start LPSLAM tracking using GUI controller.
Next, in the System tab of Varjo Base, select LPVR-DUO-Varjo
as the tracking method from the drop-down menu. Then, open the web interface (http://localhost:7119/) to configure LPVR-DUO.
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5) Setting up communication in LPVR
Navigate to the Expert Mode page in LPVR-DUO’s web interface.
Proxy ports
In the JSON
editor, set an absolute pose source for each type of pose coming from LPSLAM. Assign a freely chosen identifying name and a port
under their settings
with the type DTrack
, as shown below.
Tracking IDs
To receive the HMD poses from LPSLAM, got to the trackedObjects
section add an entry with the corresponding absoluteSource
. Then, set the tracking ID defined earlier for the VSLAM tracker and apply the configuration.
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6) Calibration of Platform IMU
To perform the IMU calibration using LPSLAM as the optical tracking system, you first need to add the reference/platform IMU under the imuSources
section in LPVR’s configuration.
In the LPVR-DUO’s web interface, navigate to the Calibration page from the bottom navigation bar. Click on the second setup option (Is your IMU tracked by the optical tracking system?) to display the corresponding calibration process.
1) LPMS-IG1 tracking setup
Select the absolute source corresponding to the Marker
tracker, and set the Tracking ID to the ID of the chosen fiducial marker.
2) Calibrate optical tracking of LPMS-IG1
Use the HMD cameras too view the fiducial marker, and the Start Calibration button will be enabled. Then, press the Start Calibration button and move the IMU with the marker in front of the cameras. The interface will display a progress bar that fills up as you change the IMU’s orientation.
Once all the required poses are obtained, the Apply Result button will appear, allowing you to apply the estimated calibration quaternion to the driver.
3) Extract IMU orientation w.r.t. space
Place the IMU back in its fixed position and ensure the marker is visible to the HMD cameras. While the marker is in view and being tracked, press the Use Current Orientation button.
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7) Full LPVR-DUO integration
Once you have successfully performed the IMU calibration, you will have a configuration similar to the example shown below.
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You can first map your environment and then disable the mapping function in LPSLAM’s Map Viewer. This is particularly useful in in-car scenarios where you only want the HMD to track its pose using only in-car visual features. However, it is not fully necessary if you are using the processor type ThresholdImage
.
Adjust Coordinates
Due to the Visual-SLAM nature of LPSLAM, the origin of its coordinate system is defined by the initial tracked pose, as shown in the image below.
As a result, if the HMD was misaligned with the world frame at startup, the XR content will also be misaligned. To correct this, navigate to the Expert Mode page of the LPVR-DUO web interface and click the Show additional functions button below the JSON editor.
Within the additional functions, navigate to Adjust Coordinates (Development Only). While the HMD positioned in the desired alignment, press the Set Current Pose as Origin button. The scene or XR content will align automatically.
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