Offline IMU Calibration for Temperature Bias Correction
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Solution Overview
Problem
Inertial measurement units (IMUs) in motion-tracking devices, such as those used for augmented reality (AR) experiences, suffer from biases that vary with temperature, making accurate motion tracking challenging due to mechanical deviations in gyroscopes and accelerometers.
Innovation Solution
An offline calibration method is employed to generate and update a calibration model by capturing IMU measurements during idle periods, correlating biases with temperatures, which are then used to correct IMU measurements during active use, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If IMU measurements are taken during active use, then motion tracking data is available, but temperature-induced biases reduce measurement accuracy
Solution Approach 1:
The system performs calibration measurements during idle periods before active use begins, establishing baseline bias values at different temperatures. This preliminary action allows the model to be updated with accurate bias data without interfering with subsequent motion tracking operations, resolving the contradiction by preparing correction data in advance rather than during active measurement.
Solution Approach 2:
The patent introduces a calibration model as an intermediary between the IMU measurements and the final motion tracking results. This model processes the raw measurements, applies temperature-based bias corrections, and outputs corrected data. The intermediary model separates the bias correction function from the motion tracking function, allowing accurate measurements even when temperature variations occur during active use.
2Measurement precision
If calibration is performed during idle periods, then measurement accuracy improves, but device productivity decreases due to calibration time
Solution Approach 1:
The system performs calibration periodically during idle periods rather than continuously or only at manufacturing. This periodic calibration approach balances the need for accurate measurements with device availability, updating the bias model at appropriate intervals without preventing the device from being used in between calibration events.
Solution Approach 2:
Calibration is performed in advance during idle periods when the device is not being used for motion tracking. This preliminary calibration ensures that accurate bias data is available before active use begins, eliminating the need to choose between calibration time and productivity during actual operation.
3Adaptability or versatility
If a calibration model is maintained, then temperature compensation is possible, but device complexity increases
Solution Approach 1:
The calibration model captures temperature-dependent bias parameters and uses these parameters to compensate for temperature effects during active use. By modeling the relationship between temperature and bias, the system adapts to different thermal conditions without requiring complex hardware modifications, achieving temperature compensation through software-based parameter adjustment.
Data Source
AI summary
Offline calibration of an inertial measurement unit (IMU) can determine biases in the motions measured by the IMU while it is not in use. The offline calibration uses an expected motion measurement based on a motionless IMU as a reference from which the biases can be computed for a temperature. The bias and the temperature can be stored in a thermal table that can be updated and expanded over multiple calibration sessions to include the biases for a range of temperatures. A model relating the biases to temperature may be created based on the thermal table. For example, a curve-fit equation relating the bias as a function of temperature may be computed based on the values in the thermal table.