IMU Sensor Fusion for Foldable Hinge Rotation
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Solution Overview
Problem
Foldable electronic devices face challenges in accurately processing signals from multiple sensors due to varying angles of rotation between lids, leading to inconsistent sensor data accuracy.
Innovation Solution
Implementing multiple inertial measurement units (IMUs) in different lids of a foldable device, detecting the angle of rotation between them, and applying a rotation matrix to adjust and combine sensor data to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple IMUs are implemented in different lids of a foldable device, then the coverage and sensing capability are improved, but the data consistency and accuracy deteriorate due to varying rotation angles between lids
Solution Approach 1:
A sensor processing unit acts as an intermediary between the multiple IMUs in different lids. It receives sensor data from each IMU, applies rotation matrices based on detected rotation angles to transform the data into a common coordinate system, and combines the transformed data. This intermediary processing resolves the coordinate system misalignment caused by varying lid angles, maintaining measurement precision while preserving the enhanced sensing capability of multiple IMUs.
2Device complexity
If sensor data from multiple IMUs is combined without rotation adjustment, then the processing complexity is reduced, but the accuracy of combined sensor data deteriorates
Solution Approach 1:
The system performs preliminary rotation angle detection and coordinate transformation before combining sensor data from multiple IMUs. By pre-aligning the data from different lids into a common coordinate system using rotation matrices, the system ensures that subsequent data combination operations maintain high accuracy. This preliminary action prevents the need for complex post-processing corrections while preserving measurement precision.
3Measurement precision
If rotation matrix transformation is applied to align sensor data, then the measurement accuracy is improved, but the computational complexity increases
Solution Approach 1:
The system changes the parameter representation of sensor data by applying rotation matrices that transform coordinates based on detected rotation angles. This parameter transformation aligns data from different lids into a common reference frame, significantly improving measurement accuracy. The computational complexity is managed by efficiently calculating rotation matrices from detected angles and applying them systematically to the sensor data streams.
Data Source
AI summary
A foldable electronic device includes a first lid and a second lid rotatably coupled together by a hinge. A first inertial measurement unit (IMU) is implemented in the first lid and generates first sensor data. A second IMU is implemented in the second lid and generates second sensor data. A sensor processing unit detects the rotation angle between the first and second lids and generates rotated second sensor data by adjusting the second sensor data based on the rotation angle. The sensor processing unit generates combined sensor data by combining the first sensor data with the rotated second sensor data. The combined sensor data is more accurate than either the first sensor data or the second sensor data.