Conference: AIrTonomy
Lead PI:
Sabine Brunswicker
Abstract
Autonomous aerial vehicles (AAVs) including drones can solve societal grand challenges such as rapid delivery of medicine and wildfire protection in a completely new way. However, a major technical challenge remains: Today?s AAVs lack the artificial intelligence (AI) needed to safely operate in real-world urban air mobility environments. In such environments, AAVs operate in proximity of urban infrastructures (e.g. buildings), at low altitude, without much regulatory oversight, and under unpredictable conditions such as unexpected weather change or additional vehicles in the field. <br/><br/>This 2-day workshop will bring together researchers working in academia, industry labs, and governmental agencies to discuss and refine uses cases and capabilities that are key elements of a research infrastructure designed to support the rapid evolution of advanced air autonomy algorithms and systems. Such an infrastructure is envisioned to enable rapid integration and testing of research community components using a cyber and physical infrastructure that can support both in-person and remote operation. An initial implementation of an AAV research infrastructure is AirTonomy located at Purdue University. The workshop will invite a diverse group of individuals including potential users from academia, representatives of industry partners as well as national, state, and regional governments. Through pre-conference activities and in-person breakout sessions, the workshop participants will identify: 1) research use cases, 2) technical requirements of a large-scale research infrastructure, and 3) concepts for sustainability. After the workshop, a report will be published online, and a task force assembling a lead user community will assist with the finalization of research infrastructure requirements and design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Performance Period: 06/01/2024 - 11/30/2024
Award Number: 2419443