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Jan30
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Join us January 30 for "Grand Challenges in Robotics: Dexterity," https://lnkd.in/gEDYgBGA an interactive webinar discussing how progress in robotic materials is impacting the field of manipulation. The second conversation in the series, hosted by Northwestern's Center for Robotics and Biosystems.
Grand Challenges in Robotics: Dexterity
Conversation 2 on Robotic Dexterity: Novel Materials for Robust Grasping and Manipulation
Monday, January 30, 3-4 p.m. CSTModerator: Carmel Majidi, Carnegie Mellon University
Panelists: Elliot W. Hawkes, UC Santa Barbara; Tess Hellebrekers, Meta AI; Nancy Pollard, Carnegie Mellon University; Yon Visell, UC Santa BarbaraNovel material architectures capable of matching the mechanics, sensing capabilities, and articulated motions of natural human hands have the potential for transformative impact in robotic grasping and manipulation. Such advancements build on efforts to combine research in dexterous manipulation and haptics with emerging methods in soft robotics and integrated material systems. In this panel, experts from these domains will discuss and debate how progress in robotic materials is impacting the field of manipulation.
Register: https://lnkd.in/gEDYgBGA
Conversation 1 on Dexterity, from Jan 11, 2023, can be viewed at https://lnkd.in/gbjysTd2
TIME Monday, January 30, 2023 at 3:00 PM - 4:00 PM
CONTACT Amy Nedoss amy.nedoss@northwestern.edu EMAIL
CALENDAR Center for Robotics and Biosystems (CRB)
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Feb3
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Join the Center for Robotics and Biosystems (CRB) for the February Speaker Series
Speaker: Bradly Stadie, Assistant Professor of Statistics, Northwestern University
Date and Time: Friday, February 3 at 12:00 p.m. CT
Location: Tech B211 and Zoom
Zoom Link: https://tinyurl.com/CRBSeminar
• NU-authenticated attendees will be automatically admitted. Others, please email amy.nedoss@northwestern.edu to be admitted from the waiting room.Abstract:
How should we train reinforcement learning agents that are capable of abstract planning? One recent technique that has shown much promise is Search on the Replay Buffer. In this technique, agents treat a buffer of past experience as nodes on a graph and execute a graph search algorithm. The result of this search is a sequence of known good states that an agent can use to navigate its environment. There are two obvious shortcomings with this approach. 1) If we assume we can transition between every pair of states, then the complexity of the path planning problem is exponential in the size of the buffer. 2) Exploration over different possible paths remains a challenge, even if we prune the number of nodes.Towards overcoming these shortcomings, we introduce L3P, an algorithm for learning latent landmarks for planning. This algorithm learns landmarks in a latent space, where the distance between graph nodes is optimized to equal the number of steps it takes to transition between environmental states. We introduce a novel clustering algorithm that forces states that are close in this metric to cluster together, reducing our buffer to a few representative latent landmarks. Finally, we wrap up by considering cold diffusion approaches to solving this path planning problem. We show that sequence planning over a buffer can be recast as a diffusion model, and introduce the notion of Maximum Entropy Subgoal Skipping (MESS) to help with exploration.
Bio:
Bradly Stadie's research explores techniques for developing general machine intelligence. Recently, foundational models such as GPT-3 have provided a promising avenue towards training intelligent machines. In particular, these foundational models show that we can leverage large quantities of unsupervised data to learn a latent underlying structure of a data space. In this latent space, planning and abstract reasoning become much more tractable.
In spite of its promise, there does not currently exist a GPT-3 equivalent in Reinforcement Learning. The current leading method, learning a dynamics model to predict the agent's next state, and then using this model to bootstrap a planning or curiosity module, has proven ineffective. Dr. Stadie’s current research proposes an enticing alternative: that goal-reaching should be used as the foundational model for reinforcement learning. The idea is as follows: they want agents to learn in an unsupervised fashion how to generate and reach various goal states in their environments. They can then bootstrap from this goal-reaching ability, breaking complex goals into a series of simpler tasks. This will endow agents with the ability to plan and reason over long time horizons, an essential capacity for the emergence of general intelligence. There exists a deep relationship between unsupervised goal-reaching and imitation learning, which frequently comes up in his research. From time to time, he also uses various tools from graph search, causal inference, and generative networks.TIME Friday, February 3, 2023 at 12:00 PM - 1:00 PM
LOCATION Mechanical Engineering, B211, Technological Institute map it
CONTACT Amy Nedoss amy.nedoss@northwestern.edu EMAIL
CALENDAR Center for Robotics and Biosystems (CRB)
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Feb6
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Dr. Mary Frecker
Distinguished Speaker
Professor of Mechanical & Biomedical Engineering
Penn State University
Abstract - Compliant mechanisms have been the subject of intense research in recent decades. Making compliant mechanisms “smart” to form flexible, adaptive structures is the focus of my research group, with applications ranging from medical devices to aerospace structures. This seminar will describe recent work on modeling approaches for compliant mechanisms with both superelastic material behavior and large deformations, which have not been considered previously in the literature. This approach allows for design of compliant mechanism-based metamaterials with highly nonlinear stiffness and enhanced energy absorption. Additionally, the presentation will cover our method for designing active compliant mechanisms that change shape on demand due to application of external stimulus such as magnetic field, electric field, or temperature. Methods to optimize origami-based designs with magneto active elastomer and dielectric elastomer materials will be described, along with an analytical modeling approach for soft magneto active elastomer devices produced via additive manufacturing.
Bio - Mary Frecker is the Head of the Department of Mechanical Engineering, a Professor of Mechanical Engineering and Biomedical Engineering, the Leighton Riess Chair in Engineering, and the founding director of the Center for Biodevices at Pennsylvania State University. She has served as Associate Department Head for Graduate Programs in Mechanical & Nuclear Engineering, as well as Director of the Bernard Gordon Learning Factory in the College of Engineering. Dr. Frecker has a B.S. from the University of Dayton, and an M.S. and Ph.D. in Mechanical Engineering from the University of Michigan. Dr. Frecker has been awarded the Pearce Endowed Development Professorship in Mechanical Engineering at Penn State, the GM/Freudenstein Young Investigator Award by the American Society of Mechanical Engineers (ASME) Mechanisms Committee (2002), the Outstanding Advising Award by the Penn State Engineering Society (2002), the Outstanding Research Award by the Penn State Engineering Society (2005), three ASME Best Paper awards (2009 and 2015), and the ASME Adaptive Structures and Material Systems Award (2021). She served as an Executive Leadership in Academic Technology & Engineering (ELATE) Fellow in 2018-2019, and completed the Changing the Future for Senior Women Faculty in STEM leadership program in 2019. Dr. Frecker is a Fellow of the ASME, is currently an Executive Committee member of the ASME Design Engineering Division and past Chair of the ASME Mechanisms & Robotics Technical Committee, and has served as Associate Editor of the ASME Journal of Mechanical Design, Chair of the ASME Adaptive Structures and Material Systems Technical Committee, and Executive Committee member of the ASME Aerospace Division.
TIME Monday, February 6, 2023 at 3:00 PM - 4:00 PM
LOCATION ITW, Ford Motor Company Engineering Design Center map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)
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Mar11
EVENT DETAILS
lessWinter Classes End
TIME Saturday, March 11, 2023
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar18
EVENT DETAILS
lessSpring Break Begins
TIME Saturday, March 18, 2023
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar24
EVENT DETAILS
lessWinter Degrees Conferred
TIME Friday, March 24, 2023
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar