Robot Camera Calibration Updates for Drift-Aware Motion Control
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Solution Overview
Problem
Existing camera calibration methods for robot control become outdated due to changes in camera properties or environmental conditions over time, leading to errors in robot operations.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 defined 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is performed initially, then the robot can perform operations based on camera images, but the calibration becomes outdated over time due to changes in camera properties or environmental conditions
Solution Approach 1:
The system performs camera calibration periodically by capturing calibration images at specified locations and comparing them to initial calibration data. This periodic update mechanism ensures calibration accuracy is maintained over time without requiring continuous manual intervention, resolving the contradiction between maintaining reliability and avoiding excessive time loss.
Solution Approach 2:
The robot performs self-calibration by automatically capturing calibration images, comparing them to initial calibration data, and determining deviations without requiring continuous manual operator intervention. The system serves itself by detecting when calibration updates are needed and executing the update process autonomously.
2Reliability
If periodic camera calibration updates are performed, then accurate calibration information is maintained, but the system complexity increases
Solution Approach 1:
The system captures calibration images, compares them to initial calibration data, and uses the comparison results to determine whether calibration updates are needed. This feedback mechanism automatically adjusts the calibration process based on actual conditions, maintaining accuracy without requiring overly complex manual intervention systems.
Solution Approach 2:
The patent introduces an intermediary calibration image comparison process that mediates between the camera system and the robot control system. By using calibration images as an intermediary, the system can automatically assess calibration accuracy and trigger updates only when necessary, reducing overall system complexity.
3Measurement precision
If the robot moves the calibration pattern to multiple locations, then comprehensive calibration data is collected, but the calibration process time increases
Solution Approach 1:
The system captures calibration images at multiple locations within the camera field of view, but only performs full calibration processing when the deviation from initial calibration exceeds a threshold. This partial action approach ensures comprehensive data collection when needed while avoiding unnecessary time consumption during normal operation.
Solution Approach 2:
The system changes the parameter being measured from full calibration processing to simple deviation comparison. By comparing calibration images to initial calibration data and only triggering full recalibration when deviations exceed thresholds, the system maintains measurement precision while significantly reducing the time required for routine checks.
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.