Robot Camera Calibration Verification During Idle Periods
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robot systems face inaccuracies in operation due to outdated camera calibration information, which can result from changes in camera properties or environmental relationships over time, leading to errors in robot positioning and task execution.
Innovation Solution
A robot control system that performs automatic verification of camera calibration by comparing reference images with verification images captured at different times, using a verification symbol to determine deviation parameters and trigger updates to calibration information when thresholds are exceeded, ensuring accurate robot operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration operation is performed by a person, then calibration information can be obtained, but the process is time-consuming and prone to human error
Solution Approach 1:
The robot performs calibration verification autonomously by moving the verification symbol to reference locations and capturing images automatically. The control system compares verification images with reference images to detect calibration deviations without human intervention, enabling the system to self-verify and self-correct calibration status.
Solution Approach 2:
The system performs calibration verification during idle periods before actual robot operations begin. By proactively checking calibration status in advance, the system prevents calibration-related errors from affecting production operations and schedules updates without disrupting workflow.
2Reliability
If calibration verification is performed frequently, then calibration accuracy is maintained, but system complexity and computational load increase
Solution Approach 1:
The control system implements a feedback mechanism where verification images are compared with reference images to detect calibration deviations. When deviations exceed a threshold, the system triggers calibration updates and notifies operators, creating a closed-loop system that maintains reliability without requiring continuous complex monitoring.
Solution Approach 2:
The system performs partial verification by checking only critical reference locations and comparing key features in verification images against reference images. This selective approach maintains calibration reliability while reducing computational complexity compared to full-system verification.
3Measurement precision
If robot operations are paused for calibration updates, then calibration accuracy is improved, but productivity decreases
Solution Approach 1:
The system performs calibration verification during idle periods before robot operations begin. By proactively detecting calibration deviations in advance, the system schedules updates during non-productive time, preventing calibration-related interruptions during actual operations and maintaining productivity.
Solution Approach 2:
The feedback mechanism detects calibration deviations and triggers updates only when necessary, avoiding unnecessary pauses in production. The system notifies operators of calibration status, enabling them to schedule updates during planned maintenance windows rather than interrupting ongoing operations.
Data Source
AI summary
A computing system and a method for calibration verification is presented. The computing system is configured to perform a first calibration operation, and to control a robot arm to move a verification symbol to a reference location. The robot control system further receives, from a camera, a reference image of the verification symbol, and determines a reference image coordinate for the verification symbol. The robot control system further controls the robot arm to move the verification symbol to the reference location again during an idle period, receives an additional image of the verification symbol, and determines a verification image coordinate. The robot control system determines a deviation parameter value based the reference image coordinate and the verification image coordinate, and whether the deviation parameter value exceeds a defined threshold, and performs a second calibration operation if the threshold is exceeded.