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.
About this Dataset
| Title | Data for "Estimating Uncertainty in Robot Kinematics and Pose Measurements with Expectation-Maximization" |
|---|---|
| Description | 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. |
| Modified | 2023-07-18 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Robot Calibration , Laser Tracker Uncertainty , Pose Uncertainty , Hybrid Manipulator |
{
"identifier": "ark:\/88434\/mds2-3049",
"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "Benjamin Moser"
},
"programCode": [
"006:045"
],
"landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3049",
"title": "Data for \"Estimating Uncertainty in Robot Kinematics and Pose Measurements with Expectation-Maximization\"",
"description": "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.",
"language": [
"en"
],
"distribution": "",
"bureauCode": [
"006:55"
],
"modified": "2023-07-18 00:00:00",
"publisher": {
"@type": "org:Organization",
"name": "National Institute of Standards and Technology"
},
"theme": [
"Manufacturing:Robotics in manufacturing",
"Mathematics and Statistics:Uncertainty quantification"
],
"keyword": [
"Robot Calibration",
"Laser Tracker Uncertainty",
"Pose Uncertainty",
"Hybrid Manipulator"
]
}
