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Data for "Estimating Uncertainty in Robot Kinematics and Pose Measurements with Expectation-Maximization"
Included here are figures and relevant data for the work "Estimating Uncertainty in Robot Kinematics and Pose Measurements with Expectation-Maximization". We present a method to validate the measurement uncertainty of a metrology instrument without a priori estimates in the context of a kinematic calibration using Expectation-Maximization methods and extend our results to characterize post-calibration pose uncertainty for the manipulator throughout a workspace. This technique permits the robot kinematic model to be fitted simultaneously with a parameterized uncertainty model derived from direct-drive laser tracker kinematics. We demonstrate the performance of this algorithm in a simulated and experimental setting, achieving 6.4um position and 70.8 urad rotation error for kinematic calibration and statistically validating the fitted uncertainty model for points throughout the calibrated workspace.
Complete Metadata
| bureauCode |
[ "006:55" ] |
|---|---|
| identifier | ark:/88434/mds2-3049 |
| issued | 2023-08-08 |
| landingPage | https://data.nist.gov/od/id/mds2-3049 |
| language |
[ "en" ] |
| programCode |
[ "006:045" ] |
| theme |
[ "Manufacturing:Robotics in manufacturing", "Mathematics and Statistics:Uncertainty quantification" ] |