Uploaded November 2021 | Updated September 2026, 34 minutes ago
ONLINE Lockheed Martin Robotics Seminar: Towards Safe and Trustworthy Cyber-Physical Systems
Lu Feng
Assistant Professor
Department of Computer Science and Department of Engineering Systems and Environment
University of Virginia
Cyber-physical systems (CPS) are smart systems that include co-engineered interacting networks of physical and computational components. Prominent examples of CPS include autonomous robots, self-driving cars, smart cities, and medical devices. CPS are increasingly everywhere, providing new capabilities to improve quality of life and transform many critical areas. However, significant challenges are posed for assuring the safety and trustworthiness of CPS. In this talk, I will present some of my recent work to tackle these challenges, including (1) trust in human-automated vehicle interactions, (2) safe multi-agent reinforcement learning via shielding for robotic planning, and (3) predictive monitoring with logic-calibrated uncertainty for smart cities. If time allows, I will also briefly talk about my on-going research on improving the accountability and transparency of CPS.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
ONLINE Lockheed Martin Robotics Seminar: Towards Safe and Trustworthy Cyber-Physical Systems
Lu Feng
Assistant Professor
Department of Computer Science and Department of Engineering Systems and Environment
University of Virginia
Cyber-physical systems (CPS) are smart systems that include co-engineered interacting networks of physical and computational components. Prominent examples of CPS include autonomous robots, self-driving cars, smart cities, and medical devices. CPS are increasingly everywhere, providing new capabilities to improve quality of life and transform many critical areas. However, significant challenges are posed for assuring the safety and trustworthiness of CPS. In this talk, I will present some of my recent work to tackle these challenges, including (1) trust in human-automated vehicle interactions, (2) safe multi-agent reinforcement learning via shielding for robotic planning, and (3) predictive monitoring with logic-calibrated uncertainty for smart cities. If time allows, I will also briefly talk about my on-going research on improving the accountability and transparency of CPS.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
