Robot Camera Calibration Updates for Drift Detection
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Solution Overview
Problem
Existing camera calibration methods for robot control become outdated due to changes in camera properties or environmental relationships over time, leading to errors in robot operations.
Innovation Solution
A robot control system that performs periodic updates of camera calibration by capturing recent calibration images, comparing them to initial calibration data, and outputting a notification if deviations exceed a threshold, ensuring accurate camera calibration information for reliable robot operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual camera calibration is performed initially, then the robot can perform operations based on camera images, but the calibration becomes outdated over time due to changes in camera properties or environmental relationships
Solution Approach 1:
The system performs camera calibration periodically by capturing calibration images at defined locations and comparing them to initial calibration data. This periodic recalibration ensures calibration accuracy is maintained without requiring continuous manual intervention, resolving the contradiction between maintaining reliability and minimizing time loss.
Solution Approach 2:
The robot performs self-calibration by automatically capturing calibration images, comparing them to initial data, and detecting deviations without requiring manual operator intervention. This self-service approach maintains calibration accuracy while minimizing time loss compared to manual recalibration processes.
2Measurement precision
If periodic calibration updates are performed by capturing and comparing calibration images, then calibration accuracy is maintained, but the system complexity increases
Solution Approach 1:
The system monitors changes in calibration parameters by comparing recent calibration images to initial calibration data. By focusing on parameter changes rather than complete recalibration, the system maintains measurement precision while reducing the complexity of the calibration process.
Solution Approach 2:
The system implements feedback by comparing recent calibration images to initial calibration data and detecting deviations. This feedback mechanism maintains calibration accuracy through automated comparison and deviation detection, reducing the need for complex manual calibration procedures.
3Reliability
If the robot moves the calibration pattern to multiple locations within the camera field of view, then comprehensive calibration data is collected, but the calibration process time increases
Solution Approach 1:
The system performs preliminary calibration by capturing images at multiple defined locations within the camera field of view before normal operation begins. This preliminary comprehensive calibration ensures reliability without requiring time-consuming calibration procedures during productive operations.
Solution Approach 2:
The system performs comprehensive calibration periodically rather than continuously. By collecting calibration data at multiple locations during periodic updates rather than during every operation, the system maintains calibration completeness while minimizing impact on robot productivity.
Data Source
AI summary
A robot control system and a method for updating camera calibration is presented. The method comprises the robot control system performing a first camera calibration to determine camera calibration information, and outputting a first movement command based on the camera calibration information for a robot operation. The method further comprises outputting, after the first camera calibration, a second movement command to move a calibration pattern within a camera field of view, receiving one or more calibration images, and adding the one or more calibration images to a captured image set. The method further comprises performing a second camera calibration based on calibration images in the captured image set to determine updated camera calibration information, determining whether a deviation between the camera calibration information and the updated camera calibration information exceeds a defined threshold, and outputting a notification signal if the deviation exceeds the defined threshold.