In many ways, autonomy is the holy grail of artificial intelligence (AI). While tremendous advances towards this ultimate goal have been made across a number of disciplines, and for a number of applications, general-purpose autonomy remains elusive. Indeed, even when we focus on specific classes of applications, such as autonomous driving, numerous gaps remain. One fundamental challenge shared by many autonomous systems is to ensure that autonomous behavior is trustworthy: that is, safe, reliable, secure, and fair. This planning grant is a stepping stone towards an AI institute devoted to foundational and use-inspired advances in TRustworthy Autonomous Systems Engineering. The institute would be focused on four research themes: 1) trustworthy AI integration in autonomous systems, 2) trustworthy platforms for real-time AI in autonomous systems, 3) trustworthy multiagent systems, and 4) accountable autonomy. Each of these will yield important advances in understanding the design of trustworthy systems in which AI is embodied in an open-loop framework involving perception, planning, and control. Furthermore, these advances will be coupled with use-inspired research in areas such as autonomous driving and drones, creating a virtuous cycle with applications directing fundamental research, and benefiting directly from it.

This project will aim to create a community of stakeholders---the TRASE Innovation Ecosystem---focusing on trustworthy autonomous systems, with implications for a broad range of applications, from autonomous driving to autonomous flight. In addition, the institute will yield transformative educational advances in the form of new materials for courses and programs that train students in the design and analysis of autonomous systems. The vision is to develop innovative educational components, such as competitions, and integrated student-industry-research teams that coalesce around common TRASE-relevant problems. Finally, educational collaborations will be established with minority-serving institutions, such as St Louis Community College (Florissant Campus) to broaden participation in computing in general, and in trustworthy autonomous systems engineering in particular.

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.

Project Start
Project End
Budget Start
2020-09-01
Budget End
2022-08-31
Support Year
Fiscal Year
2020
Total Cost
$500,000
Indirect Cost
Name
Washington University
Department
Type
DUNS #
City
Saint Louis
State
MO
Country
United States
Zip Code
63130