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Group name seminar
Title
Summary Design of Robotics and Embedded systems, Analysis, and Modeling Seminar
Description

Design of Robotics and Embedded systems, Analysis, and Modeling Seminar (DREAMS)

Spring 2017

The Design of Robotics and Embedded systems, Analysis, and Modeling Seminar (DREAMS) occurs weekly on Mondays from 4.10-5.00 p.m. in 250 Sutardja Dai Hall.

Similar to last year, DREAMS has joined forces with the Control Theory Seminar and the CITRIS People and Robots Seminar CPAR.

The Design of Robotics and Embedded systems, Analysis, and Modeling Seminar topics are announced to the DREAMS list, which includes the chessworkshop workgroup, which includes the chesslocal workgroup.

Information on the seminar series might be useful for potential speakers. If you have any questions about DREAMS, please contact Markus N. Rabe. If you want to subscribe to our mailing list, please drop me a line.

Seminars from previous semesters can be found here.

Schedule

Ioannis Paschalidis January 27, 2017
Julie Shah February 13, 2017
Marjan Sirjani February 24, 2017 UPCOMING
Rajeev Joshi February 27, 2017 UPCOMING
Brian Lathrop March 03, 2017 UPCOMING
Clark Barrett March 06, 2017 UPCOMING
Sergey Levine March 13, 2017 UPCOMING
Stanley Osher March 20, 2017 UPCOMING
Tim Salcudean April 03, 2017 UPCOMING
Parvez Ahammad April 10, 2017 UPCOMING
Steven Shladover April 17, 2017 UPCOMING
Necmiye Ozay April 24, 2017 UPCOMING
Stefano Carpin May 01, 2017 UPCOMING

Data-Driven Price-of-Anarchy Estimation in Transportation Networks

Jan 27, 2017, 10-11am, 380 Soda, Ioannis Paschalidis, Boston University.

Slides

Abstract

Equilibrium modeling is common in a variety of fields such as game theory, transportation science, and systems biology. The inputs for these models, however, are often difficult to estimate, while their outputs, i.e., the equilibria they are meant to describe, are often directly observable. By combining ideas from inverse optimization with the theory of variational inequalities, we develop an efficient, data-driven technique for estimating the parameters of these models from observed equilibria. A distinguishing feature of our approach is that it supports both parametric and nonparametric estimation by leveraging ideas from statistical learning.

We apply this general framework to transportation networks. Using real traffic data from the Boston area, we estimate origin-destination flow demand matrices and the per-road cost (congestion) functions drivers implicitly use for route selection. Given this information, one can formulate and solve a system-optimum problem to identify socially optimal flows for the transportation network. The ratio of total latency under a user-optimal policy versus a system-optimal policy is the so-called Price-of-Anarchy (POA), quantifying the efficiency loss of selfish actions compared to socially optimal ones. We find that POA can be quite substantial, sometimes exceeding 2, suggesting that there is scope for control actions to steer the equilibrium to a socially optimal one. We will discuss what some of these actions may be and how to prioritize interventions.

Bio:

Yannis Paschalidis is a Professor of Electrical and Computer Engineering, Systems Engineering, and Biomedical Engineering at Boston University. He is the Director of the Center for Information and Systems Engineering (CISE). He obtained a Diploma (1991) from the National Technical University of Athens, Greece, and an M.S. (1993) and a Ph.D. (1996) from the Massachusetts Institute of Technology (MIT), all in Electrical Engineering and Computer Science. He has been at Boston University since 1996. His current research interests lie in the fields of systems and control, networks, applied probability, optimization, operations research, computational biology, medical informatics, and bioinformatics.

Prof. Paschalidis' work has been recognized with a CAREER award from the National Science Foundation, the second prize in the George E. Nicholson competition by INFORMS, and a finalist best paper award in the IEEE International Conference on Robotics and Automation (ICRA). His work on protein docking has been recognized for best performance in modeling selected protein-protein complexes against 64 other predictor groups. Work with students has won a best student paper award at the 9th Intl. Symposium of Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, an IBM/IEEE Smarter Planet Challenge Award, and an IEEE Computer Society Crowd Sourcing Prize. He was an invited participant at the 2002 Frontiers of Engineering Symposium organized by the National Academy of Engineering, and at the 2014 National Academies Keck Futures Initiative (NAFKI) Conference. Prof. Paschalidis is a Fellow of the IEEE and the Editor-in-Chief of the IEEE Transactions on Control of Network Systems.


Enhancing Human Capability with Intelligent Machine Teammates

Feb 13, 2017, 4-5pm, 250 SDH, Julie Shah, MIT.

Slides

Abstract

Every team has top performers -- people who excel at working in a team to find the right solutions in complex, difficult situations. These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it. Similarly, even when a machine can do the job better than most of us, it can’t explain how. In this talk I share recent work investigating effective ways to blend the unique decision-making strengths of humans and machines. I discuss the development of computational models that enable machines to efficiently infer the mental state of human teammates and thereby collaborate with people in richer, more flexible ways. Our studies demonstrate statistically significant improvements in people’s performance on military, healthcare and manufacturing tasks, when aided by intelligent machine teammates.

Bio:

Julie Shah is an Associate Professor in the Department of Aeronautics and Astronautics at MIT and leads the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory. In 2014, Shah was recognized by the National Science Foundation with a Faculty Early Career Development (CAREER) award and by MIT Technology Review on its 35 Innovators Under 35 list. Her work on industrial human-robot collaboration was also in Technology Review’s 2013 list of 10 Breakthrough Technologies. She has received international recognition in the form of best paper awards and nominations from the ACM/IEEE International Conference on Human-Robot Interaction, the American Institute of Aeronautics and Astronautics, the Human Factors and Ergonomics Society, the International Conference on Automated Planning and Scheduling, and the International Symposium on Robotics. Shah earned degrees in aeronautics and astronautics and in autonomous systems from MIT.


Can We Trust Self-Driving Cars? Adaptive Timed Actors for Building Dependable Cyberphysical Systems

Feb 24, 2017, 2-3pm, 540 Cory Hall, Marjan Sirjani, Mälardalen University.

Slides

Abstract

In this presentation I will not talk about self-driving cars. I put the phrase in the title to catch your attention. I will talk about models, techniques and tools that can be used to build dependable cyberphysical systems (and hence be able to trust self-driving cars). A family of actor-based languages are introduced to enable model driven development and provide a faithful and usable model for building distributed, asynchronous, and event-based systems with least effort. Network and computational delays, periodic events, and required deadlines can be expressed in the model. Model checking and simulation tools are built based on the formal semantics of the language. For deadlock-freedom and schedulability analysis special efficient techniques in state space exploration is proposed by exploiting the isolation of method execution in the model. I will show how these models can be used in safety assurance and performance evaluation of different systems, like Network on Chip architectures, sensor network applications, Traffic Control systems, and quadricopters. I show a general pattern in track-based traffic control systems, and a framework where self-adaptive actors are used to address self-adaptive traffic control systems.

Bio:

Marjan Sirjani joined Malardalen University in June 2016 as a Professor and the Chair of the Software Engineering group. She is also a part-time Professor at School of Computer Science at Reykjavik University. Her main research interest is applying formal methods in Software Engineering. She works on modeling and verification of concurrent, distributed and cyberphysical systems. Marjan and her research group are pioneers in building model checking tools, compositional verification theories, and state-space reduction techniques for actor-based models. Marjan has been the PC member and PC chair of several international conferences including SEFM, Coordination, FM, FMICS, ICFEM, MEMOCODE, and FSEN. Before joining academia as a full-time faculty she has been the managing director of Behin System Company for more than ten years, developing software and providing system services. Marjan served as the head of the Software Engineering Department of School of Electrical and Computer Engineering at the University of Tehran prior to joining the School of Computer Science at Reykjavik University in 2008. She visited Ptolemy group at UC Berkeley as a Fulbright Scholar in 2015 and her research is currently focused on safety assurance and performance evaluation of autonomous cyberphysical systems, in which she is collaborating with Ptolemy group.


The Bugs that went to Mars and Terrorized Earth

Feb 27, 2017, 4-5pm, 250 SDH, Rajeev Joshi, NASA JPL.

Slides

Abstract

Since its dramatic landing in Gale crater in August 2012, the Curiosity Rover has been busy exploring the surface of Mars, looking for evidence of past habitable environments. Having completed over 4 years on Mars, and with nearly 17 kms on its odometer, Curiosity has already made historic discoveries, finding evidence of an ancient freshwater streambed, organic molecules and other key ingredients necessary for life. Yet, in spite of its great successes, the mission has not been without a few hiccups. In this talk, we discuss the most significant of these: the Sol-200 anomaly, when the failure of a flash memory chip uncovered three latent software bugs that nearly killed the mission. We describe how the anomaly manifested itself, how recovery was achieved, and lessons learnt from the experience. The work described in this talk was carried out at Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Bio:

Rajeev Joshi is a Principal Engineer at the Lab for Reliable Software at NASA's Jet Propulsion Laboratory, where he works on building and applying tools based on formal methods to improve mission software reliability. He is also currently the Chief Engineer for Flight Software and Avionics Systems at JPL. He was a member of the Curiosity rover flight software development team, and, after landing, a member of the surface operations team, serving as data management chair and supporting anomaly investigations. For his work on Curiosity, he received two JPL Mariner Awards and the NASA Exceptional Achievement Medal. He holds a B.Tech in Computer Science from the Indian Institute of Technology, Bombay, and an MS/PhD (also in Computer Sciences) from the University of Texas at Austin. His previous employment includes 4 years at the DEC/Compaq/HP Systems Research Center (SRC) in Palo Alto, CA, and 2 years at AT&T Bell Labs in Murray Hill, NJ. He is an elected member (and current secretary) of IFIP Working Group 2.3 on Programming Methodology.


3+1 - An HMI Design Framework for Autonomous Vehicles

Mar 03, 2017, 2-3pm, 540 Cory, Brian Lathrop, Volkswagen of America, Electronics Research Lab.

Slides

Abstract

While mode confusion and the ensuing human error that goes with it will likely have a significant impact on the safety of future AVs, the transitioning between modes and how those transitions are orchestrated via the vehicle’s HMI will be equally important. This is particularly relevant when the modes to which one is transitioning are not discrete states (e.g., on and off). That is, when transitions are put into the context of SAE Driving Automation Definitions it becomes clear that the human operator will transition into partial automation, conditional automation, and high automation. These variable states of the vehicle need to be communicated in a timely and clear manner, and the orchestration of the transitions between states needs to be effortless and exact.

Bio:

Senior Principal Scientist Brian Lathrop is the Senior Principal Scientist for the Technology and Trend Scouting team at Volkswagen. In 2003 Brian received his Ph.D. in Cognitive Science from the University of California, Santa Cruz. In 2004 Brian joined VW and was responsible for human factors and usability testing activities for infotainment and driver assistance systems. In 2008 Brian became the senior manager of the HMI team at the ERL, responsible for defining the vision, roadmap, and overall strategy. He has led many projects focused on reinventing the vehicle cockpit of tomorrow, realizing advanced infotainment controls, futuristic displays, gaze and gesture-dependent interfaces, and HMI concepts for self-driving cars. In 2016 Brian joined the Technology and Trend Scouting, focused on transforming customer insights into user friendly products.


TBA (Clark Barrett)

Mar 06, 2017, 4-5pm, 250 SDH, Clark Barrett, Stanford/Google.

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TBA (Sergey Levine)

Mar 13, 2017, 4-5pm, 250 SDH, Sergey Levine, UC Berkeley.

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TBA (Stanley Osher)

Mar 20, 2017, 4-5pm, 250 SDH, Stanley Osher, UCLA.

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TBA (Tim Salcudean)

Apr 03, 2017, 4-5pm, 250 SDH, Tim Salcudean, University of British Columbia.

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TBA (Parvez Ahammad)

Apr 10, 2017, 4-5pm, 250 SDH, Parvez Ahammad, Instart Logic Inc..

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TBA (Steven Shladover)

Apr 17, 2017, 4-5pm, 250 SDH, Steven Shladover, UC Berkeley.

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TBA (Necmiye Ozay)

Apr 24, 2017, 4-5pm, 250 SDH, Necmiye Ozay, University of Michigan.

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TBA (Stefano Carpin)

May 01, 2017, 4-5pm, 250 SDH, Stefano Carpin, UC Merced.

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Administrators Christopher Brooks cxh cxh@eecs.berkeley.edu
Sadigh Dorsa dsadigh dsadigh@berkeley.edu
Markus N. Rabe rabe
Mary Stewart marys
Members Christopher Brooks cxh cxh@eecs.berkeley.edu
Daniel Bundala bundala
Sadigh Dorsa dsadigh dsadigh@berkeley.edu
Markus N. Rabe rabe
Mary Stewart marys
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