Project Grant 2528914
- This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) will provide $150,000 to Wright State University to advance fundamental knowledge in intelligent and sustainable air-ground collaborative systems. The project aims to develop a unified framework that enables seamless collaboration between aerial drones and ground vehicles through efficient data handling, enhanced scene understanding, and adaptive mission planning. Key...
- This National Science Foundation Project Grant of $322,886 supports the establishment of a new Research Experiences for Undergraduates site at Embry-Riddle Aeronautical University focused on networking research for drone swarms in the age of artificial intelligence and machine learning. Over three years, the project will engage eight undergraduate students per summer in research activities under the guidance of experienced mentors. Key areas of focus include dynamic network management, network...
- This $280,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, titled "COLLABORATIVE RESEARCH: CISE CROSSCUTTING SMALL: CPS: AI-POWERED AUTONOMOUS SYSTEMS FOR DYNAMIC IN-AIR OPERATIONS", will support research to enable unmanned aerial vehicles (UAVs) to physically interact with moving objects in mid-air. The project aims to develop: 1) physics-informed modeling to improve UAV flight dynamics prediction, 2)...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $198,583 to East Texas A&M University to develop a deep analytics framework for location integrity and awareness in unmanned aerial vehicle (UAV) operations. The project aims to create a complementary solution to GPS-based methods for UAV navigation, utilizing trajectory-based analysis and deep learning techniques to enhance reliability in challenging conditions such as limited GPS...
- This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $150,000 to the University of Alabama to develop an advanced autonomous drone system equipped with thermal imaging and artificial intelligence (AI) capabilities. The goal is to quickly and accurately detect energy loss in residential building envelopes, integrating the drone system with a digital twin (DT) model to visualize and plan energy...
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $400,000 Project Grant to The Trustees of Princeton University, Office of Research and Project Administration, under the NSF Computer and Information Science and Engineering (CFDA 47.070) program. This 3-year grant supports collaborative research on developing theories and algorithms for scalable multi-agent planning and control to enable safe and robust autonomous electrical vertical take-off and...
- This Project Grant awarded by the National Science Foundation's STEM Education program (CFDA 47.076) aims to develop an advanced extended reality (XR) training system that combines Federal Aviation Administration (FAA) Part 107 regulations and unmanned aircraft systems (UAS) operation, powered by generative artificial intelligence (AI) assistance. The $399,871 project, titled "Transforming Compliance Training for Drone Operators Through an Extended Reality and Generative Artificial...
- This $300,000 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will fund research by the Regents of the University of California at Riverside (UC Riverside) to develop trustworthy and resilient coordination mechanisms for multi-agent systems. The project aims to enable autonomous systems like drones, vehicles, robots, and smart infrastructure to reliably work together, even when facing uncertainty, failure, or...
- This $300,000 Project Grant was awarded by the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports a collaborative research project between California State University San Marcos (CSUSM), a Hispanic Serving Institution, and other partners to develop an integrated and extensible platform for investigating security vulnerabilities and countermeasures in the emerging paradigm of...
- This $519,563 federal Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund research to develop new mathematical tools and algorithms that enable large groups of autonomous agents, such as drones and ground robots, to operate safely, efficiently, and collaboratively. The central focus is on modeling these multi-agent systems as evolving spatial distributions rather than individually, enabling the design of scalable and practical algorithms...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $599,961 to the University of Massachusetts to develop a new framework called AERIAL (AI-Embedded Responsive Intelligent Agents with Trajectory-Induced Digital Twin Learning). The project aims to improve the safety, speed, and efficiency of drone missions that support public safety and national resilience. The research will introduce a new AI-driven mathematical model called the Trajectory-Induced Graph to enable drones and robots to collaborate intelligently by combining advanced mathematics with artificial intelligence. The project will also leverage a virtual simulation of the real world (a digital twin) to help the agents plan and adapt their paths as situations evolve. In addition, the project includes hands-on educational opportunities for college and high school students. The award period is from August 1, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 7/16/25 |