IMU Coordinate Alignment via Steady-State Rotation Matrix
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Solution Overview
Problem
Current methods for aligning positioning systems with inertial measurement units (IMUs) in virtual, augmented, and mixed reality require high hardware quality and complexity, limiting application scenarios and increasing costs, especially when multiple position objects are involved.
Innovation Solution
An alignment method that determines 3D positions and IMU calculation positions when the IMU enters and exits a steady state, using relative vectors and rotation matrices to align the coordinate systems of position devices and IMUs, reducing hardware process requirements and costs by eliminating the need for multiple position objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple position objects are used to speculate pose and derive alignment relationship, then the alignment accuracy between IMU and controller can be improved, but the hardware process quality requirements increase exponentially and the structural design is limited
Solution Approach 1:
The patent extracts the alignment calibration function from the position objects themselves and implements it through software processing of IMU data. Instead of using multiple position objects to derive alignment, the system uses a single position object combined with IMU steady-state detection to obtain rotation matrices, thereby eliminating the need for multiple position objects and reducing hardware complexity while maintaining alignment accuracy.
Solution Approach 2:
The patent replaces the mechanical approach of using multiple position objects with a sensor-based system. By substituting the mechanical positioning system with an IMU-based system that detects steady states and calculates rotation matrices, the patent achieves alignment calibration without the complexity of multiple position objects, effectively replacing mechanical complexity with sensor processing.
2Measurement precision
If multiple position objects are combined to derive alignment relationship, then the pose speculation accuracy can be improved, but the cost increases exponentially
Solution Approach 1:
The patent uses a single, simple position object combined with the IMU sensor to achieve alignment calibration. Instead of requiring multiple expensive position objects, the system relies on the IMU's ability to detect steady states and compute rotation matrices, thereby reducing the cost of hardware while maintaining the necessary calibration accuracy.
Solution Approach 2:
The patent extracts the alignment calibration capability from the position objects and relocates it to the IMU processing system. By doing so, the system no longer needs multiple position objects, reducing both hardware cost and complexity while achieving the same calibration function through software-based IMU data processing.
3Stability of the object's composition
If position device and IMU are rigidly bound together, then the alignment stability can be improved, but the positioning system cannot be separated from the IMU and application scenarios are limited
Solution Approach 1:
The patent introduces dynamic steady-state detection to the alignment calibration process. Instead of requiring a fixed rigid connection, the system dynamically identifies steady states during operation and uses these transient moments to calculate and update rotation matrices. This allows the position device to be flexibly connected to the IMU while maintaining alignment stability through continuous calibration during steady-state periods.
Solution Approach 2:
The patent performs alignment calibration in advance during steady-state periods before actual positioning operations begin. By pre-calculating rotation matrices when the system is stationary or in steady state, the system prepares the alignment relationship beforehand, ensuring stability during dynamic operation without requiring a rigid permanent connection, thereby enabling flexible application scenarios.
Data Source
AI summary
An alignment method is provided. A first 3D position and a first IMU calculation 3D position of a position object with an IMU is determined when the IMU enters a steady state. A second 3D position and a second IMU calculation 3D position of the position object is determined when the IMU exits the steady state. A first relative vector is determined based on the first 3D position and the second 3D position. A second relative vector is determined based on the first IMU calculation 3D position and the second IMU calculation 3D position. A rotation matrix is determined based on the first relative vector and the second first relative vector. A coordinate system of the position device is aligned with a coordinate system of the IMU based on the rotation matrix. An electronic device and a non-transitory computer readable storage medium are also provided.