Project Grant 2515359
- 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 $300,000 Project Grant under the Engineering program (CFDA 47.041) to Washington State University (WSU) for a 3-year collaborative research project. The project advances the theory and methods for developing computationally lightweight control algorithms that ensure the safe and reliable operation of autonomous systems in safety-critical applications. The research aims to expand the applicability of Control Barrier Function (CBF) methods to...
- This National Science Foundation (NSF) project grant award under the Engineering program (CFDA 47.041) will support fundamental research to develop new methods for generating control barrier functions for safety-critical autonomous systems. The $460,632 award to the University of Colorado will fund a 3-year research effort to address the knowledge gap in systematically designing constrained control laws that can provably guarantee safety while maximizing system performance. The research team...
- This $500,000 Project Grant was awarded on May 1, 2025 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 project, titled "CPS: SMALL: LIFTED HYBRIDIZATION: A NEW REPRESENTATION FOR EFFICIENT CONTROL AND VERIFICATION OF CYBER-PHYSICAL SYSTEMS", seeks to develop new theories, algorithms, and tools to enable more effective and robust control of...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, provides $600,000 to the Regents of the University of Michigan to develop a comprehensive framework for end-to-end verification of control systems. The key objectives are to bridge the gap between high-level control theory and low-level implementation, and to provide formal proofs of correctness for common controllers like PID and model predictive...
- 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 $315,000 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of new methods to robustly analyze and control large-scale networked systems with uncertain and variable delays. Specifically, the project will combine integral quadratic constraint and partial integral equation frameworks to enable accurate modeling and control of nonlinear systems with known and uncertain delay components. This work has direct applications...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $500,000 to Carnegie Mellon University to develop techniques for mitigating various risks in the control of autonomous systems operating in uncertain and interactive environments. The five-year project, awarded on July 1, 2025, aims to: 1) quantify long-term risks despite latent variables and limited data, and 2) develop efficient control techniques that provide long-term assurance...
- This Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems supports research to develop low-complexity, safe learning-enabled algorithms for partially observable nonlinear systems with uncertain dynamics. The $400,000 award to Michigan State University aims to accomplish two key objectives: 1) Propose direct data-driven learning approaches for backup safe control policies in partially observable nonlinear systems, and 2) Introduce...
- This federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $550,000 to Carnegie Mellon University (CMU) to advance research on sampling-based optimal control methods for real-time decision-making in complex robotic and autonomous systems. The project aims to develop new mathematical frameworks to better understand, analyze, and improve these flexible and scalable control methods, which can handle highly nonlinear and discontinuous...
This Project Grant award from the National Science Foundation (CFDA 47.041 - Engineering) provides $300,000 in funding to the Regents of the University of Michigan to advance the theory and methods underlying the development of computationally lightweight control algorithms that ensure the safe and reliable operation of autonomous systems in safety-critical applications. The project aims to expand the applicability of control barrier functions (CBFs) through the development of a novel class of parametric CBFs, establishing a rigorous theoretical foundation for their onboard implementation. The research is expected to benefit a broad range of industrial uses, including autonomous drone delivery, robotics, manufacturing, transportation, autonomous driving, and precision agriculture. The award has a performance period from September 1, 2025 to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 8/18/25 |