Collaborative Research: Parametric Control Barrier Functions For Complex Modern Safety-Cri — NSF Award to Washington State Univers
This project advances 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. Such methods can benefit a broad range of industrial uses, including autonomous drone delivery, rob
| Award title | Collaborative Research: Parametric Control Barrier Functions For Complex Modern Safety-Cri |
|---|---|
| Award ID | 2515358 |
| Awardee | Washington State University |
| City | PULLMAN |
| State | WA |
| Amount obligated | $300,000 |
| Principal investigator | Mehdi Hosseinzadeh |
| Program | EPCL: Energy, Power, Control, |
| Start date | 09/01/2025 |
| Abstract | This project advances 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. Such methods can benefit a broad range of industrial uses, including autonomous drone delivery, robotics, manufacturing, aerial and ground transportation, autonomous driving, and precision agriculture. To fully realize their benefits, autonomous systems must be capable of making |
| Source | NSF Awards |
$799/mo
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