Galvanometer Scanner Angle Estimation for Accurate 3D Point Clouds
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Solution Overview
Problem
Galvanometer-based angle measurement noise in beam scanning systems degrades the accuracy of 3D point clouds, requiring complex signal processing and increased bandwidth/power, and traditional low-pass filtering removes important information.
Innovation Solution
A dynamic model of the galvanometer-based two-dimensional scanner is used to remove angle measurement noise, generating accurate estimated angle measurements for improved 3D point cloud generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional low-pass filtering is applied to reduce galvanometer angle measurement noise, then noise is reduced, but important information is removed and measurement precision deteriorates
Solution Approach 1:
The patent changes the approach from frequency-domain filtering to time-domain prediction by using a dynamic model. Instead of applying low-pass filtering that removes high-frequency components, the system uses the dynamic model to predict the expected angle based on the driving signal and compares it with the noisy measurement, thereby removing noise while preserving the actual angle information through parameter transformation rather than simple frequency filtering
Solution Approach 2:
The patent replaces the traditional signal processing approach (low-pass filtering) with a model-based prediction approach. By substituting the mechanical filtering method with a dynamic model prediction method, the system achieves noise reduction without losing important angle information, as the dynamic model captures the true angle trajectory based on the driving signal
2Reliability
If complex signal processing is used to handle angle measurement noise, then noise attenuation is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent implements a self-service mechanism where the dynamic model uses the existing driving signal (which is already available in the system) to predict the angle measurement. This eliminates the need for separate complex signal processing circuits or additional sensors, as the system uses its own operating parameters to generate the corrected angle information, thereby reducing device complexity while maintaining noise attenuation capability
Solution Approach 2:
The dynamic model acts as an intermediary between the driving signal and the noisy angle measurement. Instead of directly processing the noisy measurement through complex filtering algorithms, the system uses the dynamic model as a mediator to translate the driving signal into the expected angle trajectory, simplifying the overall signal processing architecture
Data Source
AI summary
A beam scanning method includes generating a first driving signal based on a first angle setpoint; generating a second driving signal based on a second angle setpoint; driving a two-dimensional scanner about a first scanning axis based on the first driving signal and about a second scanning axis based on the second driving signal; generating a distance measurement based on a reflected light beam; generating a first estimated angle measurement signal based on the first angle setpoint and a dynamic model of the two-dimensional scanner; generating a second estimated angle measurement signal based on the second angle setpoint and the dynamic model of the two-dimensional scanner; associating the distance measurement with a first estimated angle value corresponding to the first estimated angle measurement signal; and associating the distance measurement with a second estimated angle value corresponding to the second estimated angle measurement signal.