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When you pick up one pencil from a pile on a table, how does your hand know where to go or what to grab? Your eyes help out. For robots to do the same, they
Objective To develop and deploy measurement science that advances manufacturing robotic system performance, collaboration, agility, autonomy, safety, and ease of implementation to enhance U.S. innovation and industrial competitiveness. Technical Idea The fundamental idea is to provide the
Objective To facilitate the adoption of AI-based robotic approaches in practical manufacturing scenarios by creating test methods that target AI-enabled robotic systems, evaluating the performance of AI-enabled robotic systems, and creating manufacturing-relevant and AI-centric datasets. Technical
Objective To develop measurement science for characterizing sensing and perception system performance to reduce the risks of adopting these technologies and to advance the agility, safety, and productivity of collaborative, industrial, and mobile robots. Technical Idea Over the past 5 years, the
Prem Rachakonda, Abhilash Mane, Craig I. Schlenoff, Kamel S. Saidi
Evaluating perception sensor systems for on-road autonomous vehicles is still fraught with ambiguity due to the varying and dynamic environmental factors that
Prem Rachakonda, Kamel S. Saidi, Marek Franaszek, Helen Qiao, John Sweetser, Armin Khatoonabadi, David Dechow, Wesley Rhodes
NIST is leading and supporting multiple efforts to develop standards for 3D imaging systems for manufacturing automation applications. Many manufacturers
Mitchell R. Woodside, Patrick Bazzoli, Philip A. Olubodun, J. Adam Nisbett, Helen Qiao, Douglas A. Bristow
While there are many works developing methods for modeling and calibrating robot kinematics, assessing the accuracy of those models has received little
Marek Franaszek, Helen Qiao, Kamel S. Saidi, Prem Rachakonda
The ASTM E2919-22 standard provides a test method for evaluating 3D scanners for static pose. This standard was developed in conjunction with the industry and
Traditional camera calibration methods compute camera intrinsic parameters from a set of target features with known geometries. The most common target is a