Magnetic Sensor Calibration Using VIO for Automatic Field Correction
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Solution Overview
Problem
Existing methods for calibrating magnetic sensors on user devices require inconvenient user actions, such as making figure-eight patterns, to correct for internal magnetic fields, making regular calibration impractical.
Innovation Solution
Utilizing visual inertial odometry (VIO) data to determine the orientation of the client device and compute a device correction vector, which accounts for internal magnetic fields, allowing for regular calibration without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional figure-eight calibration method is used, then magnetic sensor calibration accuracy is improved, but user convenience deteriorates due to requiring repeated manual motions
Solution Approach 1:
The system performs magnetic sensor calibration automatically using visual inertial odometry data without requiring user intervention. The device self-calibrates by comparing magnetic field measurements with orientation data from visual and inertial sensors, eliminating the need for manual figure-eight motions while maintaining calibration accuracy.
Solution Approach 2:
The patent replaces the mechanical manual calibration process with an automated computational approach. Instead of requiring physical figure-eight motions, the system uses visual inertial odometry algorithms to determine device orientation and computes correction vectors automatically, substituting mechanical user actions with computational processing.
2Reliability
If frequent calibration is performed using traditional methods, then orientation accuracy is improved, but user time consumption increases due to repeated manual operations
Solution Approach 1:
The device performs automatic calibration in the background without requiring user time investment. The system continuously or periodically calibrates the magnetic sensor using visual inertial odometry data, maintaining high orientation accuracy while consuming zero user time since no manual intervention is needed.
Solution Approach 2:
The calibration process operates continuously or periodically without interruption to user activities. The system maintains continuous calibration capability by constantly comparing magnetic field measurements with visual-inertial orientation estimates, ensuring orientation accuracy is maintained over time without requiring discrete calibration sessions.
3Measurement precision
If manual calibration is required, then calibration precision is improved through controlled motions, but device complexity increases due to calibration instruction systems
Solution Approach 1:
The patent extracts the calibration computation from the user interaction layer and places it entirely in the automated sensor processing layer. By removing the need for calibration instruction systems and user guidance interfaces, the device reduces software complexity while maintaining calibration precision through automated visual-inertial-magnetic sensor fusion.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables frequent and automatic calibration of magnetic sensors by correcting for internal device fields, improving orientation accuracy in augmented reality applications.
Implementation Method 1
the magnetic field measurements may include an observed magnetic field vector representing the measured magnetic field by the client device's magnetic sensor
Implementation Method 2
The client device uses visual inertial odometry (VIO) data to calibrate a magnetic sensor on the client device. The client device uses VIO to determine the orientation of the client device when the client device captures magnetic field measurements.
Data Source
AI summary
The present disclosure describes a method for calibrating a magnetic sensor of a client device. The method may include receiving a set of magnetic field measurements, each of which includes a device location, an orientation of the client device, and an observed magnetic field vector measured by the magnetic sensor. The method may include computing a device correction vector for the client device based on the set of magnetic field measurements. For each magnetic field measurement, the method includes determining a world magnetic field vector at the device location of the magnetic field measurement, computing an expected measured magnetic field vector at the device location, accessing an estimated device correction vector for the client device, computing an expected adjusted vector for the client device, comparing the observed magnetic field vector associated with the magnetic field measurement and the expected adjusted vector, and computing the device correction vector based on the comparison.