This $274,354 National Science Foundation project grant funds research at the University of Nevada, Reno to develop techniques for improving the resilience of vision-guided unmanned aerial vehicles and other autonomous systems against cyberattacks. The grant is part of the NSF's Engineering program (CFDA 47.041), which supports innovation and excellence in engineering research.
Specifically, the research aims to advance an observability analysis framework for detecting and responding to stealthy attacks that simultaneously target mission planning, control, perception, and sensor data for safety-critical applications involving transportation, aerospace, and military systems. The project will enhance reliability of vision-guided autonomous systems like self-driving cars and networked aerial vehicles by hardening them against cyber threats. Evaluation will rely on experiments with quadcopters in an indoor laboratory as well as advanced simulation software. Broader impacts include integrating research into graduate courses and engaging undergraduate and K-12 students in STEM education outreach using robotic demonstration platforms.
Generated 1/6/24, 12:25 PM