basalt/doc/monado/Vive.md

# Valve Index, HTC Vive, and other lighthouse-tracked headsets

The integration with Basalt for the `vive` driver in Monado is on early stages.

Many things do not work very well yet.

# Calibration

The most annoying bit is that you will need to manually calibrate the headset to
get a json file for Basalt like the [index_calib.json](/data/index_calib.json)
example. You can use that example first to see how it works for you by setting
`SLAM_CONFIG=$bsltdeps/basalt/data/monado/index.toml`, but that will likely not
work very well.

The general calibration procedure is as follows:

1. Setup the calibration target:
    1. Download [the one from kalibr](https://drive.google.com/file/d/1DqKWgePodCpAKJCd_Bz-hfiEQOSnn_k0/view)
    2. Open the pdf file and measure with a ruler the black square side (e.g., 24 inch 1080p screen, 34% zoom in Okular viewer, gives 3cm)
    3. Update aprlgrid_6x6.json "tagSize" property in meters (e.g., 3cm would be "0.03")
2. Record camera calibration sequence with the euroc recorder in Monado:
    - See calib-cam3 example from TUM-VI https://vision.in.tum.de/data/datasets/visual-inertial-dataset
    - Or this example from ORB-SLAM3: https://www.youtube.com/watch?v=R_K9-O4ool8
    - Note that for stereo calibration you want to cover as much as possible of
      both cameras images but always trying to keep >90% of the calibration target
      visible in both views. This can be a little tricky so practice it beforehand.
3. Record camera-imu calibration sequence: (faster motions)
    - Similar recommendations as in the previous sequence but this time we want
      faster motions that excite all IMU axes, see these examples:
    - calib-imu1 from TUM-VI https://vision.in.tum.de/data/datasets/visual-inertial-dataset
    - Or this from ORB-SLAM3 https://www.youtube.com/watch?v=4XkivVLw5k4
4. Now run camera calibration as explained [here](https://gitlab.freedesktop.org/mateosss/basalt/-/blob/xrtslam/doc/Calibration.md#camera-calibration)
5. Then camera+imu (no mocap) calibration as explained [here](https://gitlab.freedesktop.org/mateosss/basalt/-/blob/xrtslam/doc/Calibration.md#camera-imu-mocap-calibration)
6. If the datasets are not good, the calibration will likely not be very good as
   well. If you want to be sure you calibrated things properly, a good idea is
   to repeat this process until you get similar results.