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  • AME Seminar

    Wed, Oct 11, 2023 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Michael Yip, UCSD

    Talk Title: Teaching a Robot to Perform Surgery: From 3D Image Understanding to Deformable Manipulation

    Abstract: Robot manipulation have made massive strides in the past few years, especially in grasping for warehouse logistics, due to the achievements in the computer vision and reinforcement learning communities. One area that has taken off much slower is in understanding how to manipulate deformable objects. For example, surgical robotics are used today via teleoperation from a human-in-the-loop, but replacing the human visual understanding and task performance with an AI remains a lofty and puzzling challenge. How do you build intuition and control of how to deform, stretch, or cut anatomical tissue, find hemorrhages and suction blood and bodily fluids from view, or simply localize your robot within a dynamically changing and deformable world in real-time?

    In this talk, I will discuss our work that originates from trying to automate robotic surgery, but falls towards building new modeling and learning schemes for deformable robot manipulation and visual servoing. I will discuss how we analyze a multimodal spectrum of sensory information to solve real-to-sim and sim-to-real problems, while towing a fine line between physics-based models and the less-explainable yet highly successful latent space embeddings. I will show how these techniques apply not only to automating surgical robots but general robot manipulation in real-world scenes.

    Biography: Michael Yip is an Associate Professor of Electrical and Computer Engineering at UC San Diego, IEEE RAS Distinguished Lecturer, Hellman Fellow, and Director of the Advanced Robotics and Controls Laboratory (ARCLab). His group currently focuses on solving problems in data-efficient and computationally efficient robot control and motion planning through the use of various forms of learning representations from imitation learning and reinforcement learning strategies. These techniques focus on solving problems with visually guided robot manipulation and locomotion on novel, dexterous platforms, including surgical robot manipulators, continuum robots, snake-like robots, and underwater systems. His work has been recognized through several best paper awards and nominations at ICRA and IROS, and RA-L, as well as recognitions including the NSF CAREER award and the NIH Trailblazer award. Dr. Yip was previously a Research Associate with Disney Research Los Angeles in 2014, a Visiting Professor at Stanford University in 2019, and a Visiting Professor with Amazon Robotics\' Machine Learning and Computer Vision group in Seattle, WA in 2018. He received a B.Sc. in Mechatronics Engineering from the University of Waterloo, an M.S. in Electrical Engineering from the University of British Columbia, and a Ph.D. in Bioengineering from Stanford University.

    Host: AME Department

    More Info: https://ame.usc.edu/seminars/

    Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8

    Location: Seaver Science Library (SSL) - 202

    WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

    Event Link: https://ame.usc.edu/seminars/

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