Perception systems are a key component of modern autonomous cyber-physical systems (CPS), from self-driving vehicles to autonomous robots and drones. For instance, for a self-driving vehicle, perception systems provide functionalities such as estimating the state of the vehicle, building a map of obstacles in its surroundings, and detecting and tracking external objects and pedestrians. As exemplified by recent self-driving car accidents, perception failures can cascade to catastrophic system failures and compromise human safety. Therefore, the development of trustworthy perception systems is paramount to ensure safety and enable adoption of high-integrity and safety-critical CPS applications. This project lays the foundations of certifiable perception by developing a toolkit of theory, algorithms, and implementations to monitor and drastically reduce subsystem and system-level failures of perception. In particular, this project will (i) develop a new class of certifiable perception algorithms that operate reliably in challenging conditions, are equipped with input-output contracts describing their functionalities, and can formally assert contract satisfaction; (ii) show how to use certifiable algorithms to design contracts for and enable self-supervision of learning-based subsystems; (iii) design system monitors that assert the satisfaction of safety requirements or trigger fail-safe procedures in case of failure; (iv) develop a testbed and real demonstrations of certifiable perception on self-driving car data, focusing on key perception functionalities, such as vehicle localization, environment mapping, and object tracking. This research advances the state of the art in CPS and creates a new research field at the boundary between CPS, robotics and autonomous vehicles, computer vision, machine learning, system-level design and runtime verification. Certifiable perception will have a transformative impact on a broad range of autonomous CPS where safety, reliability, security, and accountability are key requirements. These include intelligent transportation, supply chain logistics (e.g., last-mile delivery), new aerospace concepts (e.g., autonomous spacecraft, flying taxis, and drones for national security), service and domestic robotics, and collaborative manufacturing. This impact will be enhanced through the release and dissemination of open-source implementations and teaching material, and via demonstrations on real testbeds. The project also boosts K-12, undergraduate, and graduate education, by supporting and actively engaging students in research activities, and through outreach efforts targeting high school students from underrepresented and underserved communities. This project is in response to the NSF CAREER 20-525 solicitation. 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.
Abstract
Luca Carloni
Luca Carloni is an Associate Professor of Computer Science at Columbia University in the City of New York, where he leads the System-Level Design Group. He holds a Laurea Degree Summa cum Laude in Electronics Engineering from the University of Bologna, Italy, a Master of Science in Engineering from the University of California at Berkeley, and a Ph.D. in Electrical Engineering and Computer Sciences from the University of California at Berkeley.
At Berkeley Luca was the 2002 recipient of the Demetri Angelakos Memorial Achievement Award in recognition of altruistic attitude towards fellow graduate students. Luca received the Faculty Early Career Development (CAREER) Award from the National Science Foundation in 2006, was selected as an Alfred P. Sloan Research Fellow in 2008, received the ONR Young Investigator Award in 2010 and the IEEE CEDA Early Career Award in 2012.
His research interests include methodologies and tools for multi-core system-on-chip platforms with emphasis on system-level design and communication synthesis, design and optimization of networks-on-chip, embedded software and distributed embedded systems. Luca coauthored over ninety refereed papers and is the holder of one patent.
Luca is an associate editor of the ACM Transactions in Embedded Computing Systems and the Elsevier Journal of Sustainable Computing. He has served in the technical program committee of several conferences including DAC, DATE, ICCAD, and EMSOFT. In 2010 he served as technical program co-chair of the International Conference on Embedded Software (EMSOFT), the International Symposium on Networks-on-Chip (NOCS), and the International Conference on Formal Methods and Models for Codesign (MEMOCODE).
In 2013 Luca serves as general chair of Embedded Systems Week (ESWeek), the premier event covering all aspects of embedded systems and software.
Luca participates in the Gigascale Systems Research Center (GSRC).
Performance Period: 03/15/2021 - 02/28/2026
Institution: Massachusetts Institute of Technology
Sponsor: National Science Foundation
Award Number: 2044973
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Call for Presentations: 2022 HCSS
Call for Presentations: 2022 HCSS
The twenty-second annual High Confidence Software and Systems (HCSS) Conference will be held the week of May 16, 2022. We solicit proposals to present talks at the conference.
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Postdoctoral Research Position in Distributed Real-Time Systems
Postdoctoral Research Position in Distributed Real-Time Systems
PRECISE Center
School of Engineering and Applied Science
University of Pennsylvania
http://precise.seas.upenn.edu/
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META expands Facebook Protect Program
META expands Facebook Protect Program
Meta, the new name for Facebook, has expanded it’s Facebook Protect security program to journalists, government officials, human rights defenders, and activist who are often targets online. The program offers enhances security like two factor authentication and alerts for potential hacking threats. Almost 1 million accounts have turned on this protection since it came online in September 2021. It also gives members tips for improving security. #ScienceofSecurity https://thehackernews.com/2021/12/meta-expands-facebook-protect-program.html
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CPS-VO
The CPS-VO is an active resource that provides access to tools and methods emerging from the CPS research community as well as a collaboration platform and repository of information. The integrated suite of models, integration platforms, and intellectual frameworks are developed and contributed by the research community lead to a new era of low-cost, distributed and open design infrastructure.
Abstract
This CAREER project responds to an urgent need to develop mobile power distribution systems that lower deployment and operating costs while simultaneously increasing network efficiency and response in dynamic and often dangerous physical conditions. The significant need for an efficient and effective mobile power distribution system became evident during search and rescue/recovery missions following the Japan tsunami and the disappearance of the Malaysia MH370 airplane. The technology outcomes from this project will apply to a broad range of environments (in space, air, water or on ground) where the success of long-term robotic network missions is measured by the ability of the robots to operate, for an extended period of time, in highly dynamic and potentially hazardous environments. These advanced features will provide the following advantages: efficiency, efficacy, guaranteed persistence, enhanced performance, and increased success in search/rescue/recovery/discovery missions.
Specifically, this project addresses the following technology problems as it translates from research discovery toward commercial application: inflated energy use currently required when the autonomous vehicles break from mission to return to recharging station; lack of multi-robot coordination needed to take into account both fundamental hardware and network science challenges necessary to respond to energy needs and dynamic environment conditions. By addressing these gaps in technology, this work establishes the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability. Moreover, the new technology developed in this project is universally adaptable for disparate autonomous vehicles especially autonomous underwater vehicles (AUVs). In more technical terms, this project creates network optimization and formation strategies that will enable a power distribution system to reconfigure itself depending on the number of operational autonomous vehicles and recharging specifications to meet overall mission specifications, the energy consumption needs of the network, situational conditions, and environmental variables. Such a system will play a vital role in real-time controlled applications across multiple disciplines such as sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. In addition to addressing technology gaps, undergraduate and graduate students will be involved in this research and will receive interdisciplinary education/ innovation/ technology translation/ outreach experiences through: developing efficient network energy routing, path planning and coordination strategies; designing and creating experimental test-beds and educational platforms; and engaging K-12th grade students in Science, Technology, Engineering and Math including those from underrepresented groups.
This project engages Michigan Tech's Great Lake Research Center (GLRC) and Center for Agile Interconnected Microgrids (AIM) to develop experimental test-beds and conduct tests that validate the resulting methods and algorithms, and ultimately, facilitate the technology translation effort from research discovery toward commercial reality.
Performance Period: 01/01/2019 - 04/30/2020
Institution: Purdue University
Sponsor: National Science Foundation
Award Number: 1921060