This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project led by Clemson University, in partnership with Purdue University, Greenville Technical College, and several industry/professional organizations. The goal is to leverage artificial intelligence (AI) and extended reality (XR) technologies to enhance the cognitive capabilities of aviation maintenance technicians during critical aircraft inspection...
This National Science Foundation (NSF) Engineering Program (CFDA 47.041) Project Grant award in the amount of $300,000 will fund research to develop methods for optimizing sensory-motor interaction strategies to minimize pilot training duration. The principal investigator at the University of Maryland, College Park will create a pilot training platform that uses multiple synthetic actors (e.g., virtual/augmented reality goggles, motion-base platform, spatial audio headphones, haptic suits,...
This federal Project Grant award of $193,420 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at Auburn University to advance the use of virtual reality (VR) in flight training. The project aims to study the physical, functional, and cognitive characteristics of VR simulation that impact a pilot trainee's ability to efficiently and effectively learn flight skills, with the goal of validating VR as...
The National Science Foundation (NSF) Engineering Program (CFDA 47.041) awarded a $150,000 EAGER (Early-Concept Grants for Exploratory Research) project grant to The Pennsylvania State University, doing business as Penn State, to develop an AI-driven, mixed-reality-based training platform. The award aims to create a realistic, cost-effective environment for interactive task training that can benefit areas such as education, workforce development, and emergency response preparation. The...
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 $103,142 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop new knowledge on the use of emerging generative AI-enabled robot-mediated technology to support scalable and inclusive hybrid-flexible (hyflex) field-based learning environments. The project will explore proof-of-concept learning technologies to transform conventional in-person field labs into hyflex labs accessible to remote and residential students for...
This $600,000 Project Grant awarded by the National Science Foundation (NSF) Division of Computing and Communication Foundations will fund the development of an innovative aerial imaging system that incorporates state-of-the-art artificial intelligence (AI) for real-time data processing and analysis. The project, titled "CISE-MSI:DP:REAL-TIME AERIAL IMAGING WITH EDGE AI," is a collaboration between students and faculty at Norfolk State University (NSU), a minority-serving...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award of $274,727 to Changeaerial LLC will fund the integration of deep learning algorithms for UAS-based infrastructure inspection. The goal is to achieve greater performance and automation for inspecting overhead electric infrastructure, with the potential to expand to other infrastructure types like telecommunication towers, pipelines, and bridges. Key aspects include:
Integrating...
This $300,000 EAGER (Early-Concept Grants for Exploratory Research) award, provided by the National Science Foundation (NSF) Engineering program (CFDA 47.041), will fund research to develop a framework that enables anyone to safely instruct quadrotor robots in customized tasks, with a focus on the specific challenge of having a quadrotor pick up and drop off a small package from/onto a human's outstretched hand. The research effort aims to address the issues of stress and safety concerns that...
This National Science Foundation (NSF) award under CFDA 47.041 Engineering program provides $300,000 in funding from October 1, 2024 to September 30, 2026 to The University of Iowa. The project aims to develop advanced motion planning algorithms to coordinate the navigation and control of multiple manned and unmanned aircraft during landing sequences near airports. Key focus areas include: 1) Developing a numerical solver for optimal control in complex UAS environments, 2) Mathematically...
This $250,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project to enhance the cognitive capabilities of aviation maintenance technicians through the integration of artificial intelligence (AI) and extended reality (XR) technologies. The primary goal is to improve inspection processes and reduce maintenance errors that cause aircraft accidents. The award is funding research and development led by a consortium of universities, industry partners, and professional organizations including Purdue University, Clemson University, aviation companies, and technology firms. Key focus areas include: 1) understanding the human factors and behavioral impacts of integrating AI/XR into aviation maintenance workflows, 2) designing AI models and human-computer interaction paradigms to enable technicians to effectively interpret and act on AI-generated inspection recommendations, and 3) quantifying the economic feasibility and broader impacts of this technological integration across the aviation maintenance domain and adjacent sectors. The project aims to provide a transformative advancement in how maintenance technicians can leverage AI and XR to enhance their capabilities and improve aircraft safety.