CPS Events
CPSRC Seminar Series: Machine learning in oceanography: How algorithms and recent developments in underwater imaging will change the way we explore the ocean
Abstract:
The midwater region of the ocean (below the ocean surface and above the seafloor) is one of the largest ecosystems on our planet, yet remains one of the least explored. This region is home to processes and marine organisms we know almost nothing about, and necessarily links what’s happening in the atmosphere to the deepest depths of the ocean. Although significant advances in underwater vehicle technologies have improved access to midwater, methods for synthesizing this data are sorely needed as persistent observation platforms are utilized in the future. Here we present new imaging technologies (DeepPIV, an instrumentation package affixed to a remotely operated vehicle that quantifies fluid motions from the surface of the ocean down to 4000 m depths) and observational platforms (Mesobot, an autonomous underwater vehicle that uses stereo cameras to track underwater targets rated to 1000 m) that will enable investigations of the ocean’s midwaters in novel ways. Recently funded efforts to mine MBARI’s 30-year, expertly curated video database to generate an “ImageNet of the ocean” will also be presented. If successful, these efforts will lead to unprecedented observations of one of the least explored regions on our planet.
Bio:
Kakani received her PhD in Bioengineering at the California Institute of Technology and specializes in biological fluid mechanics and in situ imaging methods. She is currently a Principal Engineer and Principal Investigator at MBARI, with funding provided by the Packard Foundation and the National Science Foundation. Kakani has been named a National Geographic Emerging Explorer in 2011 and a Kavli Research Fellow in the National Academy of Sciences in 2013.
CITRIS/CPAR Control Theory and Automation Symposium | 1st NorCal Control Workshop
Symposium Theme:
Current challenges and future directions in control and automation.
CITRIS and the Banatao Institute, People and Robots Initiative (CPAR) Control Theory and Automation Symposium will be held on Friday, April 27, 2018, 10 am - 5 pm at UC Santa Cruz. This symposium will kick off the 1st NorCal Control Workshop, an annual event providing a forum to bring together students, postdocs and faculty from various universities, as well as representatives from industry, in the Northern California region working in the broad area of systems and control to share knowledge and build new connections.
This inaugural event is organized by CITRIS and the Banatao Institute, People and Robots Initiative (CPAR), and the Cyber-Physical Systems Research Center (CPSRC) at UC Santa Cruz and focuses on a timely theme to the field of systems and control. A goal of the symposium is to spark discussions leading to answers to the following questions: What are the key challenges in the development of control and automation solutions to the complex problems of today? What are unique future opportunities and problems where control and automation would play a key role? The event features two keynote talks, a panel with systems and control experts from academia and industry on current challenges and future directions, as well as a poster and networking session.
Event Program:
(with corresponding time code in video of proceedings on the CPSRC YouTube channel)
00:00 - 00:25 -- Welcome - Prof. Ricardo Sanfelice (UC Santa Cruz)
00:25 - 05:41 -- Introduction - Dean Alexander Wolfe (UC Santa Cruz)
05:58 - 20:40 Mengqiao Yu (UC Berkeley) - Making Intersections Safer with Intersection Intelligence Control System
20:49 - 35:00 -- Nathan Bucki (UC Berkeley) - Improved Quadcopter Disturbance Rejection using Added Angular Momentum
35:02 - 47:35 -- Erik Kiser (Naval Postgraduate School) - The Impact of Missions and Technologies on Contingency Base Fuel Consumption
47:42 - 01:02:50 -- Richard Shaffer (UC Santa Cruz) - Open-Loop Optimal Path Planning for a Nonlinear Flexible Double Gimbal with Parameter Uncertainty
01:02:53 - 01:13:44 -- Sina Dehghan (UC Merced) - PID2018 Benchmark Challenge: Model Predictive Control With Conditional Integral Control Using A General Purpose Optimal Control Problem Solver - RIOTS
01:13:59 - 02:12:56 -- Industry Keynote - Speaker: P.K. Menon (Optimal Synthesis Inc.) -- Title: Dynamics and Control of Air Traffic
02:13:15 - 02:14:35 -- Post-lunch Address Prof. Ken Goldberg (UC Berkeley)
02:14:36 - 02:30:12 -- Berk Altin (UC Santa Cruz) - Predictive Control of Hybrid Dynamical Systems
02:30:14 - 02:41:45 -- Gang Chen (UC Davis) - Formal Interpretation of Cyber-Physical System Performance with Temporal Logic
02:41:57 - 02:54:30 -- Pierre-Jean Meyer (UC Berkeley) - Sampled-data Reachability Analysis using Sensitivity and Mixed-monotonicity
02:54:47 - 03:11:35 -- Mo Chen (Stanford University) - A Differential Game Approach to Real-time Robust Planning
03:12:07 - 03:25:43 -- Sylvia Herbert (UC Berkeley) - Safe Control of Autonomous Dynamic Systems for Real-time Planning
03:25:45 - 04:14:00 -- Academia Keynote - Speaker: Prof. Arthur J. Krener (Naval Postgraduate School) - Title: Computational Issues in Nonlinear Control and Estimation
04:14:35 - 05:35:00 -- Panel discussion - Theme: Emerging Trends and Future Directions in Control Theory and Automation -- Panelists: Martin Sehr (Siemens), Murat Arcak (UC Berkeley), Stefano Carpin (UC Merced), Arthur J. Krener (NPS), Sanjay Lall (Stanford), P.K. Menon (Optimal Synthesis Inc.)
Watch the symposium on our YouTube channel: https://youtu.be/2AREYKF4pAE
| Attachment | Size |
|---|---|
 Slides from Prof. Arthur Krener's keynote address. | 340.18 KB |
| Example files from Prof Arthur Krener's keynote address. | 87.16 KB |
CPSRC Seminar Series: Indoor Human Information Acquisition from Physical Vibrations
Abstract:
The number of everyday smart devices (such as smart TV, Samsung SmartThings, Nest, Google Home, etc.) is projected to grow to the billions in the coming decade. The Cyber-Physical Systems or Internet of Things systems that consist of these devices are used to obtain human information for various smart building applications. Different sensing approaches have been explored, including vision-, sound-, RF-, mobile-, and load-based methods. The general problems faced by these existing technologies are their sensing requirements (e.g., line-of- sight, high deployment density, carrying a device) and intrusiveness (e.g., privacy concerns).
In this talk, I will introduce my research on non-intrusive indoor human information acquisition through ambient structural vibration, which I call ’structures as sensors’. People’s interaction with structures in the ambient environment (e.g., floor, table, door) induces those structures to vibrate. By capturing and analyzing the vibration response of structures, we can indirectly infer information about the people causing it. However, challenges remain. Due to the complexity of the physical world (both structures and people), sensing data distributions can change significantly under different sensing conditions. Therefore, accurate information learning through a data-driven approach requires a large amount of labeled data, which is costly and difficult if not impossible to obtain in sensing applications. My research addresses these challenges by utilizing physical insights to guide the sensing process. Specifically, my system can robustly learn human information from limited labeled data distributions by iteratively expanding the labeled dataset. With insights into the relationship between changes of sensing data distributions and measurable physical attributes, the expansion order is guided by measured physical attributes to ensure a high learning accuracy in each iteration.
Bio:
Shijia Pan received her Bachelor's degree in Computer Science and Technology from University of Science and Technology of China and will receive a Ph.D. degree in Electrical and Computer Engineering at Carnegie Mellon University in 2018. Her research interests include cyber-physical systems, Internet-of- Things (IoT), and ubiquitous computing. She worked in multiple disciplines and focused on indoor human sensing through ambient structural vibrations. She has published in both top-tier Computer Science ACM/IEEE conferences (IPSN, UbiComp) and high-impact Civil Engineering journals (Journal of Sound and Vibration, Frontiers Built Environment). She is the recipient of numerous awards and fellowships, including Nick G. Vlahakis Graduate Fellowship, Google Anita Borg Scholarship, Best Poster Awards (SenSys, IPSN), Best Demo Award (Ubicomp), Best Presentation Award (SenSys Doctoral Colloquium), and Audience Choice Award (BuildSys) from ACM/IEEE conferences.
Watch the seminar on our YouTube channel: https://youtu.be/1nAKUuvzUFc
CPSRC Seminar Series: What is System Identification and How Does it Relate to Estimation of System Parameters?
Abstract:
Driving an automobile involves identifying processes perceived by the driver. This presently hot topic is one of the many applications of system identification. But the mathematical ideas seem to have started with ancient astronomers predicting the seasons and even eclipses. Then mathematicians and physicists got into the act. Now even engineers are using system identification as a tool, with estimation of parameters as part of the tool.
Bio:
Since 2000, Don Wiberg has been teaching and researching at UCSC in both the Dept. of Electrical and Dept. of Computer Engineering, and was a researcher in the Center for Adaptive Optics here from 2001-2011. Don is a Life Fellow of IEEE. He retired as Professor of Engineering and Applied Science in the Electrical Engineering Department at UCLA in 1994, after 29 years there, where he was also Professor of Anesthesiology. In 1995 he served as Sen. Tom Harkin’s (Dem. IA) Legislative Assistant in Defense Appropriations, Energy, Environment, Arms Control, and Veteran’s Affairs as IEEE Congressional Fellow. He was a Fulbright Senior Fellow in Denmark in 1976-7 and in Norway in 1983-4, and he visited at DFVLR, Munich, 1969-70, U. Newcastle, Aus., 1989-90, U. Maryland, 1993-94, and Ajou U., Suwan, South Korea, 2006-07.
Watch the seminar on our YouTube channel: https://youtu.be/LBVkAHeRrcw
CPSRC Seminar Series: Embedded 3D Printing of Autonomous and Somatosensory Soft Robots
Abstract:
Recent advances in soft robotics motivate the need for new fabrication strategies that enable the heterogeneous, programmable assembly of soft matter with disparate mechanical, electrical, and/or chemical properties into functional architectures. I will introduce a free-form, multimaterial 3D printing technique for manufacturing soft robots that I developed for my Ph.D. research. In this approach, known as embedded 3D (EMB3D) printing, functional and fugitive inks are extruded through a nozzle that is translated omnidirectionally within a soft, viscoplastic matrix material that surrounds and supports the printed features (e.g. catalytic, sensing, and pneumatic networks). I will first describe how matrix material rheology, printing parameters, and print path selection influence overall print fidelity. Next, my recent work in EMB3D printing entirely soft, hardware-free robots will be highlighted. Finally, I will present our work in EMB3D printing soft somatosensitive actuators innervated with multiple conductive features for haptic, proprioceptive, and thermoceptive sensing in soft robotic end effectors. Our integrated design, materials, and manufacturing approach can be readily extended to other soft robotic systems that are entirely soft, require somatosensory feedback for improved control, or cannot be made with traditional manufacturing methods.
Bio:
Ryan Truby is a Postdoctoral Fellow at Harvard University’s John A. Paulson School of Engineering and Applied Sciences and Wyss Institute for Biologically Inspired Engineering working at the intersection of multifunctional soft materials, additive manufacturing, and soft robotics. He received his Ph.D. in Applied Physics from Harvard University in December 2017. As a National Science Foundation Graduate Research Fellow and recipient of a MRS Graduate Student Gold Award, Ryan conducted his dissertation research in Prof. Jennifer Lewis’ laboratory on 3D printing of novel soft robotic systems. These included sensorized soft robots with bioinspired sensory capabilities as well as autonomous systems like the Octobot he co-invented with collaborators from Harvard’s Microrobotics Lab. Before Harvard, Ryan attended The University of Texas at Austin, earning his Bachelors of Science in Biomedical Engineering with a Minor in Physics. His undergraduate research focused on developing a collection of optically and magnetically active nanoparticle contrast agents for selectively imaging cancer with several ultrasound-based, molecular imaging techniques. He also conducted research at M.D. Anderson Cancer Center in Houston, Texas, and Sandia National Labs’ Center for Integrated Nanotechnologies in Albuquerque, New Mexico.
Since beginning his Ph.D., Ryan has remained an active teacher. At Harvard, he served two semesters as a Teaching Fellow for BE 191 – Introduction to Biomaterials, an undergraduate course at Harvard SEAS that he helped develop with Prof. Lewis, and organized a daylong summer 3D printing workshop for middle school girls hosted by Harvard’s Materials Science and Engineering Research Center. He has also worked with the Innovation Institute in Newtonville, Massachusetts, to develop and teach both a weeklong 3D printing summer camp for middle school students and a semester-long seminar class for high school students on materials science and engineering called At the Frontiers of Materials Science – Designing Matter that Matters.
