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Objective Provide the measurement science to develop standard test methods for intelligent industrial mobility systems, including mobile and wearable robotic systems. Technical Idea This project will expand prior work on performance test methods for mobile robotic systems and wearable robots under a
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
Berk Calli, Yu Sun, Kenneth Kimble, Kaiyu Hang, Máximo A. Roa Garzón, Victor-Louis De Gusseme, Salvatore D'Avella, Francis wyffels, Andrea Cavallaro, Alessio Xompero
The Ninth Robotic Grasping and Manipulation Competition (RGMC) took place in Yokohama, Japan, during the 2024 IEEE/RAS International Conference on Robotics and
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
Omar Aboul-Enein, Henry Medeiros, Mili Shah, Ya-Shian Li-Baboud, Roger Bostelman, Ann Virts
Mobile manipulators, which are robotic systems integrating an automatic or autonomous mobile base with a manipulator, can potentially enhance automation in many
Omar Aboul-Enein, Ya-Shian Li-Baboud, Roger Bostelman, Ann Virts
Mobile manipulators, which integrate a robotic manipulator with an automatic--autonomous mobile base, have the potential to augment automation by combining the