This Project Grant award from the National Science Foundation (CFDA 47.041 - Engineering) to George Washington University in the amount of $399,998 supports research aimed at designing theories and algorithms for scalable multi-agent planning and control to enable safe and robust urban air mobility (UAM) operations using electric vertical take-off and landing (eVTOL) aircraft. The key technical objectives of the project include: 1) developing safety and robustness techniques for single-agent...
This $425,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a framework for ensuring the safety of future robotic systems. The research project, led by The Trustees of Princeton University, aims to lay the foundation for safe robot autonomy by enabling robots to continually prove the safety of their actions under a wide range of operating conditions, from complex physical...
This $500,000 project grant, awarded on January 1, 2024 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to address the urgent need for end-to-end safety in learning-enabled autonomous systems across various application scenarios, such as self-driving cars and urban air mobility. The project, titled "COLLABORATIVE RESEARCH: SLES: GUARANTEED TUBES FOR SAFE LEARNING ACROSS AUTONOMY ARCHITECTURES,"...
This $1,500,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the University of Southern California's research on safe multi-agent systems using a neurosymbolic approach. The project aims to develop new theories and algorithms for the design of safe learning-enabled multi-agent systems, with applications in areas like wildfire prevention using drone swarms and semi-automated...
The National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation awarded a $149,904 Project Grant to the University of North Carolina at Charlotte under the NSF Engineering (CFDA 47.041) program. The project aims to develop novel algorithms that enable multiple aerial robots to collaboratively build spatial maps of complex urban wind fields and exploit this information to plan safer and more efficient flight paths at building-level altitudes. This research...
This Project Grant award from the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) provides $517,612 in funding to the University of Texas at Austin to develop new foundations of scalable and resilient distributed reinforcement learning for real-time autonomous cooperation in open multi-agent systems. The project aims to design new learning and control methods that enable agents to interact effectively in open systems, adapt to time-varying environments, and be...
The National Science Foundation (NSF) awarded a $200,000 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Houston System, a Hispanic Serving Institution, for the project "COLLABORATIVE RESEARCH: CISE-MSI: DP: CNS: ENABLING ON-DEMAND AND FLEXIBLE MOBILE EDGE COMPUTING WITH INTEGRATED AERIAL-GROUND VEHICLES." The project aims to develop an innovative "Aerial-Ground Intelligent Vehicular Edge (AGILE)" system that...
The National Science Foundation Division of Information and Intelligent Systems awarded a $545,980 Project Grant to Princeton University from August 1, 2021 through July 31, 2026 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant funds research at Princeton University to develop generalization and safety guarantees for learning-based control of robots. The Computer and Information Science and Engineering program supports investigator-initiated research...
This Project Grant award of $520,013, funded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program, supports the development of a framework to increase safety in multi-agent reinforcement learning (MARL) systems. The key products and services to be delivered under this 5-year award include: Developing MARL learning algorithms that can improve performance while staying within safety boundaries, even in unfamiliar environments. Building...
This National Science Foundation (NSF) CAREER (47.041 Engineering) grant award of $425,225, effective February 15, 2025 through January 31, 2030, supports research at the University of Maryland, College Park to develop the theoretical foundations of dynamic multi-agent learning under information constraints. The research program will formally introduce concepts from control theory, such as "information structure," into the study of multi-agent learning in dynamic environments where...