Marker-Based Robot Position Correction for Vision Calibration
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Solution Overview
Problem
Existing robot systems face inaccuracies due to mechanical characteristics and calibration errors between robots and cameras, leading to failures in high-precision tasks.
Innovation Solution
A method involving the use of markers to obtain positional information from both the robot and image capturing apparatus, allowing for the calculation of correction values to improve operational accuracy by correcting for mechanical and calibration-related errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If robot vision correction is applied, then robot operation accuracy is improved, but mechanical characteristics such as backlash and calibration errors between camera and robot remain uncorrected
Solution Approach 1:
The system uses markers placed on the robot and captured by the camera to obtain actual position information, compares it with command position information, and generates correction values that are fed back to correct the robot's operation. This closed-loop feedback mechanism addresses both mechanical characteristics and calibration errors by continuously measuring and correcting positional deviations.
Solution Approach 2:
Markers serve as intermediaries between the robot and the camera. By placing markers on the robot and capturing their positions with the camera, the system creates a measurable reference that bridges the gap between mechanical position and visual position, enabling correction of both mechanical characteristics and calibration errors.
2Measurement precision
If calibration between camera and robot is performed, then relative orientation accuracy is improved, but mechanical characteristics such as backlash are not corrected
Solution Approach 1:
The system performs calibration by capturing marker positions with the camera and comparing them with robot command positions, generating correction values that account for both calibration errors and mechanical characteristics. This feedback-based calibration is more comprehensive than traditional methods as it captures actual operational deviations.
Solution Approach 2:
The system changes the calibration approach by using actual marker position measurements from the camera rather than relying solely on theoretical calibration parameters. This allows the system to capture and correct for mechanical characteristics like backlash that traditional calibration methods miss.
3Reliability
If robot mechanism correction is applied, then mechanical characteristics are corrected, but calibration errors between camera and robot remain uncorrected
Solution Approach 1:
The system merges correction for mechanical characteristics and calibration errors into a single unified correction process. By using marker-based feedback that captures both types of errors simultaneously, the system eliminates the need for separate correction procedures and achieves comprehensive positional accuracy.
Data Source
AI summary
A robot system includes a robot, an image capturing apparatus, and a control apparatus. The control apparatus obtains information about a position of a portion functioning as a marker to be obtained by the robot and information about a position of the portion functioning as the marker to be obtained by the image capturing apparatus and controls the robot based on the information about the position of the portion functioning as a marker to be obtained by the robot and the information about the position of the portion functioning as the marker to be obtained by the image capturing apparatus.