Gyroscope Scale Calibration Using Optical Flow in Consumer Robots
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Consumer robots face challenges in maintaining accurate sensor calibration due to aging effects and scale changes in gyroscopes, which affect their navigation and localization capabilities, especially in surface robotics applications.
Innovation Solution
A method and system for calibrating gyroscopes using optical flow sensors by detecting physical motion and image signals, employing techniques such as pattern frequency detection, autocorrelation of image quality, and reference mark-based calibration to derive sensor calibration parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If gyroscope measurements are used for navigation and localization, then robot movement control is enabled, but scale changes and aging effects cause calibration errors over time
Solution Approach 1:
The system uses optical flow sensors to provide feedback on actual robot displacement, comparing it with gyroscope-based odometry estimates. This feedback loop enables continuous calibration of the gyroscope scale factor, compensating for aging effects and maintaining long-term navigation accuracy without requiring external calibration equipment.
Solution Approach 2:
The robot performs self-calibration by utilizing its own optical flow sensor measurements to detect and correct gyroscope scale drift. The system autonomously identifies calibration errors through consistency checks between different sensing modalities and adjusts its internal calibration parameters without external intervention, enabling lifelong operation with maintained accuracy.
2Measurement precision
If multiple sensors are integrated for navigation, then measurement accuracy is improved, but system complexity increases
Solution Approach 1:
The system merges data from gyroscopes, accelerometers, and optical flow sensors into a unified navigation solution. By combining inertial measurements with visual odometry, the system achieves higher measurement precision than any single sensor could provide alone, while the integration is managed through a coordinated calibration framework that reduces overall system complexity.
Solution Approach 2:
The optical flow sensor serves multiple functions: it provides direct velocity measurements for navigation, enables gyroscope calibration through scale factor adjustment, and contributes to overall system accuracy. This multi-functionality reduces the need for separate calibration systems, thereby managing complexity while improving measurement precision.
3Measurement precision
If gyroscope scale is adjusted for accuracy, then navigation precision is improved, but calibration maintenance becomes more difficult
Solution Approach 1:
The system automatically performs calibration maintenance by continuously monitoring the consistency between gyroscope-based odometry and optical flow measurements. When scale drift is detected, the system self-corrects by adjusting the gyroscope scale factor without requiring user intervention or external calibration equipment, thereby maintaining high navigation precision while keeping calibration maintenance simple.
Solution Approach 2:
The system implements continuous feedback monitoring of navigation accuracy by comparing measurements from multiple sensors. This feedback mechanism automatically triggers calibration adjustments when needed, eliminating the need for manual calibration maintenance while preserving navigation precision throughout the robot's operational lifetime.
Data Source
AI summary
A method for calculating a scale factor for a gyroscope can include detecting, by a gyroscope, a physical motion of a robot, detecting, by an optical flow (OF) sensor (and/or camera), one or more image signals including information; and deriving estimates of sensor calibration parameters based on the detected physical motion and the information.