Project Grant 2502855
- This $225,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to the Regents of the University of Michigan. The grant supports research focused on developing robust and reliable control algorithms and real-time scheduling techniques for cyber-physical systems, such as autonomous vehicles and delivery drones. Key objectives include designing optimization-based control...
- The National Science Foundation (NSF) awarded a $211,348 Project Grant under the Computer and Information Science and Engineering (CISE) federal grant program to Washington State University (WSU) for the collaborative research project "Robust to Early Termination Optimization for Safe and Reliable Control of High Performance Cyber-Physical Systems." The project aims to develop new control algorithms and real-time scheduling techniques to address computational constraints and variations...
- This National Science Foundation project grant of $597,585 will fund research into co-designed control and scheduling adaptation for cyber-physical system safety and performance from April 2023 through March 2026. The award is provided through the Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education in all areas of computing, communications, and information science and engineering. Specifically, a team led by...
- This $400,000 Project Grant was awarded on August 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant is funding collaborative research by the University of Southern California (USC) to develop a scalable framework for high-assurance design of safety-critical and mission-critical cooperative autonomous agents, such as warehouse robots, delivery robots, drones, and self-driving...
- This Project Grant award, valued at $200,000.00 and awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop a scalable framework for achieving robust and assured performance of autonomous agents, such as warehouse robots, delivery robots, drones, and robo-taxis, in real-world environments. The research will integrate formal methods, reinforcement learning, and multi-agent control theory to address critical...
- This $599,943 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop techniques for more efficient and resilient real-time communications in critical cyber-physical systems like aircraft, automobiles, and industrial control networks. The key innovations include creating holistic models, algorithms, and software designs to achieve the scalability, adaptability, and resiliency...
- 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 $177,560 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new training program to equip students with essential skills for conducting research on Unmanned Aerial Systems (UAS) cyber infrastructure. The project, led by San Diego State University Foundation, involves four training modules focused on fundamental aspects of UAS including control, communication, computing, and...
- 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 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) provides $592,000 to Purdue University to support collaborative research on co-designed control and scheduling adaptation for cyber-physical system safety and performance from April 2023 through March 2026. The award aims to develop new models, analyses, infrastructure and metrics to represent and account for interdependencies between control and scheduling in...
This federal Project Grant award for $563,370.00 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award will support a collaborative research project between the Washington University in University City, Missouri and industry partners to develop robust, real-time scheduling techniques and control algorithms for safe and reliable operation of cyber-physical systems, such as autonomous vehicles and delivery drones. The research will focus on co-designing control algorithms and scheduling frameworks that can dynamically adapt to changes in computational resources, with the goal of ensuring high-quality control even when computational tasks are interrupted. The research will include hands-on experimentation with automated drone delivery applications, enabling technology transfer and providing educational opportunities for engineering students. The award period is from August 1, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $563.4k | 7/19/25 |