Abstract
This disclosure describes techniques for online self-calibration of sensors utilized in motion tracking, e.g., in an augmented/virtual/extended (AR/VR/XR) device. Based on temperature measurements recorded during device use, sensor errors (biases) of sensors included in the camera and IMU are estimated and utilized to perform self-calibration of the sensors. Sensor errors from temperature changes are estimated and are utilized for error model training and to calibrate the sensors. The calibration results are stored in a sensor temperature error model. The model is used to adjust sensor parameters and/or estimation system parameters. Head motion tracking estimates generated by the sensor fusion algorithm are adjusted based on the sensor errors. Adjustment of the head motion tracking estimates based on the sensor errors improves motion tracking accuracy by compensating for temperature-induced sensor errors directly in the sensor fusion algorithm instead of treating the errors as assumed constants.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Zhang, John and Jia, Luke, "Online Self-calibration of Camera and IMU Sensors", Technical Disclosure Commons, (January 29, 2025)
https://www.tdcommons.org/dpubs_series/7774