{"@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": ["006:55"], "contactPoint": {"fn": "Benjamin Moser", "hasEmail": "mailto:benjamin.moser@nist.gov"}, "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.", "identifier": "ark:/88434/mds2-3049", "issued": "2023-08-08", "keyword": ["Hybrid Manipulator", "Laser Tracker Uncertainty", "Pose Uncertainty", "Robot Calibration"], "landingPage": "https://data.nist.gov/od/id/mds2-3049", "language": ["en"], "license": "https://www.nist.gov/open/license", "modified": "2023-07-18 00:00:00", "programCode": ["006:045"], "publisher": {"@type": "org:Organization", "name": "National Institute of Standards and Technology"}, "theme": ["Manufacturing:Robotics in manufacturing", "Mathematics and Statistics:Uncertainty quantification"], "title": "Data for \"Estimating Uncertainty in Robot Kinematics and Pose Measurements with Expectation-Maximization\""}