Cooperative Agreement 70NANB25H083
- This $116,985 Project Grant award from the National Institute of Standards and Technology (NIST) under the Measurement and Engineering Research and Standards (CFDA 11.609) program supports the development of new methods for rapidly assessing the absolute accuracy of robotic manipulators within their workspaces. The key activities include: Developing new sampling methodologies to efficiently explore a robot's workspace and improve its position and orientation accuracies; determining the optimal...
- This Cooperative Agreement award from the National Institute of Standards and Technology (NIST) under the Measurement and Engineering Research and Standards program (CFDA 11.609) provides $198,000.00 to Carnegie Mellon University to develop methods for the validation and deployment of AI-powered robots in manufacturing applications. The key products and services to be delivered include: Development of an AI robotic information system with a generative simulation framework to automatically...
- This National Science Foundation Project Grant of $299,923 awarded on September 15, 2022 will fund the development of an open-source ecosystem for robot manipulation research through August 31, 2023. The award falls under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) which aims to advance science and technology innovation. The University of Massachusetts Lowell will establish an open-source ecosystem covering physical, digital, instructional and functional assets to...
- This five-year, $205,073 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support research at Tufts University to develop methods for transferring multisensory object knowledge across collaborative robots. The Principal Investigator will work to enable robots with different bodies, sensors and movement capabilities to learn from each other's experiences manipulating and perceiving objects through various senses. This...
- This Project Grant award, valued at $225,509.00, was provided by the National Institute of Standards and Technology (NIST) under the Measurement and Engineering Research and Standards (CFDA 11.609) Federal Grant Program. The purpose of this award is to develop novel motion planning and control algorithms that can optimize physical interactions for improved robotic manufacturing capabilities. Key activities include creating adaptive motion and task-level controllers that can compliantly execute...
- This Project Grant award from the National Institute of Standards and Technology (NIST) under the Measurement and Engineering Research and Standards (CFDA 11.609) Federal Grant Program provides $167,999 to the University of Massachusetts Lowell to develop machine learning training datasets and algorithms for manufacturing-focused grasp planning and object pose estimation. The key objectives are to gather information on machine learning tools to streamline robot programming, expand on a prior...
- This EAGER (Early-concept Grants for Exploratory Research) project, awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041), aims to create a personalized training framework that adapts to each worker's cognitive functions and sensorimotor skills in collaborative robotic manufacturing environments. The $299,953 grant, awarded on September 1, 2024, with a completion date of August 31, 2026, focuses on advancing personalized training strategies for complex...
- This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $404,441 to Texas Tech University System to conduct research on improving collaboration between humans and robots in dynamic industrial environments. The research aims to create a new generation of human-centered robotic systems that can monitor environmental conditions and human well-being in real-time, and then adaptively adjust their behavior to support more efficient and safer...
- This $150,000 Project Grant from the National Science Foundation's Office of Emerging Frontiers and Multidisciplinary Activities, under the Engineering program (CFDA 47.041), will support the development of a conceptual framework and physical testbed to advance human-robot collaboration across distributed manufacturing environments. Specifically, the Virginia Polytechnic Institute & State University will generate knowledge around how to optimize mixed teams of on-site human and robot workers...
- This $454,020 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) will support collaborative research at the University of Michigan to develop soft materials with embedded sensors, circuits, and actuators enabling a new class of intelligent soft robots. The goal is to create a soft robotic manipulator that can autonomously recognize and sort objects by their physical characteristics using only these advanced material components, without requiring...
PURPOSE: THE RESULTS OF THIS GRANT WILL LOWER THE BARRIERS FOR SMALL AND MEDIUM MANUFACTURERS TO ASSESS THE PERFORMANCE OF THEIR ROBOTIC SYSTEMS. THE PURPOSE OF THIS GRANT IS TO DEVELOP A STRUCTURED APPROACH TO DESIGN LOW-COST OPEN-SOURCE SENSORS BASED ON CAMERA SYSTEMS AND ELECTRONIC TEXTILES FOR SYSTEM EVALUATION OF ROBOTIC SYSTEMS, AS WELL AS DEVELOPING NOVEL OPEN-SOURCE MATHEMATICAL SOFTWARE THAT CAN BE IMPLEMENTED ON PORTABLE DEVICES. THIS GRANT WILL CREATE MATHEMATICAL METRICS TO COMPARE THESE FRAMEWORKS WITH CURRENT GROUND TRUTH SOURCES USED AT NIST, WHICH ARE OFTEN MORE EXPENSIVE AND IMMOBILE.ACTIVITIES TO BE PERFORMED: THE COOPER UNION WILL PERFORM THE FOLLOWING:DESIGN LOW-COST OPEN-SOURCE SENSORS, BASED ON CAMERA SYSTEMS AND ELECTRONIC TEXTILES, FOR EVALUATION OF ROBOTIC SYSTEMSDEVELOP NOVEL OPEN-SOURCE MATHEMATICAL SOFTWARE THAT CAN BE IMPLEMENTED ON WIDELY AVAILABLE DEVICES, SUCH AS LAPTOPS AND MOBILE PHONES.CREATE MATHEMATICAL METRICS TO COMPARE THESE FRAMEWORKS WITH CURRENT, OFTEN MORE EXPENSIVE AND IMMOBILE GROUND TRUTH SOURCES FOUND AT NIST.EXPECTED OUTCOMES: THE GRANT WILL FOCUS ON IMPLEMENTING A SENSOR FRAMEWORK AND DEVELOPING THE SUPPORTING MATHEMATICAL SOFTWARE. THIS INCLUDES COLLABORATION WITH EL PERSONNEL TO COLLECT DATA AND COMPARE IT AGAINST NIST GROUND TRUTH SYSTEMS. THE RESEARCH WILL ALSO EXPLORE INNOVATIVE METHODS FOR REGISTERING TOOLS WITH GROUND TRUTH SYSTEMS. ALL FINDINGS WILL BE THOROUGHLY DOCUMENTED AND DISSEMINATED THROUGH PEER-REVIEWED JOURNAL ARTICLES AND CONFERENCE PRESENTATIONS.INTENDED BENEFICIARIES: THE BENEFICIARIES WILL BE SMALL AND MEDIUM MANUFACTURERS. ROBOTIC SYSTEMS ARE INTEGRAL TO MODERN MANUFACTURING, AND ENHANCING THEIR PERFORMANCE AND SAFETY IS CRITICAL TO ADVANCING U.S. INNOVATION AND COMPETITIVENESS. THIS GRANT WILL SUPPORT THE DEVELOPMENT LOW-COST, OPEN-SOURCE FRAMEWORKS AND ROBUST MATHEMATICAL METRICS FOR EVALUATING THE CAPABILITIES OF MANUFACTURING ROBOTIC SYSTEMS.SUBRECIPIENT ACTIVITIES: THE RECIPIENT DOES NOT INTEND TO SUBAWARD FUNDS.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $90.0k | 8/8/25 |