Robot Calibration Point Selection for Joint Deflection and Backlash
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Solution Overview
Problem
Existing robot calibration techniques struggle to accurately discriminate and identify joint deflection and backlash, leading to poor calibration accuracy due to their dependency on joint torque direction.
Innovation Solution
A correction device that generates candidate points based on a robot mechanism model and end effector information, determining measurement points where joint torque meets a threshold, and calculates mechanism error parameters to minimize position errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If joint deflection and backlash are not discriminated and identified separately, then calibration can be performed with simpler methods, but calibration accuracy deteriorates due to inability to distinguish these angle errors
Solution Approach 1:
The patent segments the angle errors into distinct components: joint deflection and backlash. By generating multiple candidate points with different joint torque directions and identifying measurement points where torque thresholds are met, the system separates the identification of these two error types. This segmentation enables accurate discrimination and identification of each error component independently, resolving the contradiction between measurement precision and device complexity.
2Measurement precision
If measurement points are selected without considering joint torque threshold, then calibration process is simpler, but ability to discriminate joint deflection and backlash deteriorates
Solution Approach 1:
The patent changes the selection criterion for measurement points from arbitrary or uniform distribution to being based on joint torque threshold parameters. By calculating joint torque for each candidate point and selecting only those points where torque meets or exceeds the threshold, the system ensures that measurement points are strategically chosen to enable discrimination of joint deflection and backlash. This parameter-based selection improves measurement precision while maintaining operational simplicity through automated calculation.
Data Source
AI summary
A correction device includes: a measurement point generation unit configured to generate a plurality of candidate points corresponding to posture of a robot within a movable range of the robot based on robot mechanism model information representing a mechanism of the robot and end effector information concerning an end effector installed in the robot, and determine, among the generated plurality of candidate points, a candidate point at which joint torque τ of each joint of the robot in the posture corresponding to each candidate point is equal to or more than a predetermined threshold as a measurement point; and a parameter identification unit configured to calculate a position error between a calculated position and a measured position of the end effector in the posture corresponding to the measurement point and identify mechanism error parameters so that the calculated position error is minimized.