MEMS Reflector Trajectory Prediction for AR Displays
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Solution Overview
Problem
Biresonant MEMS reflectors in scanning projector displays face challenges in predicting instantaneous tilt angles due to thermal drifts and vibrational coupling between oscillations, affecting the accuracy of image projection in virtual and augmented reality applications.
Innovation Solution
A controller is configured to oscillate the biresonant MEMS reflector about X and Y axes, obtaining information on tilt angles over time, determining future tilt angles using sync signals, and employing statistical or analytical models, including neural networks, to predict the reflector's trajectory and adjust the light source's power accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If biresonant MEMS reflector is used for scanning, then scanning speed and energy efficiency are improved, but prediction accuracy of instantaneous tilt angles deteriorates due to thermal drifts and vibrational coupling
Solution Approach 1:
The system employs feedback mechanisms where the controller continuously receives information about tilt angles at different moments of time and uses this feedback to evaluate and predict future tilt angles, compensating for thermal drifts and vibrational coupling effects that occur during high-speed scanning
Solution Approach 2:
The controller predicts future tilt angles of the MEMS reflector based on past tilt angle information before the actual scanning position is reached. This preliminary action allows the system to pre-adjust or compensate for expected deviations caused by thermal drift and vibrational coupling, maintaining measurement precision during high-speed operation
2Measurement precision
If trajectory prediction is performed to compensate for time lags, then image projection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system changes the parameter of using past tilt angle information and time differences to predict future positions, rather than attempting real-time calculation of complex physical effects. This parameter change approach simplifies the computational model while maintaining prediction accuracy for trajectory compensation
Data Source
AI summary
A controller for a tiltable MEMS reflector is configured to oscillate the reflector about X axis or about X and Y axes, and to obtain information about current and past tilt angles. The controller is configured to evaluate tilt angles of the tiltable MEMS reflector at a later moment of time based on the previously obtained information about the tilt angles of the tiltable MEMS reflector at the different earlier moments of time. The controller may be further configured to energize the light source providing a light beam to the tiltable MEMS reflector at the later moment of time with brightness and color corresponding to the brightness and color of a pixel that will be painted by the tiltable MEMS reflector at the later moment of time. A statistical model may be combined with machine learning to accurately predict future tilt angles of the tiltable MEMS reflector.