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Events for February 26, 2008

  • Weekly Seminar Series on Eng. Neuroscience & Health/CRES

    Tue, Feb 26, 2008 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    University Calendar


    Hosted by: Professor Mataric and Valero"Data-Driven Grasping and Manipulation"Speaker: Professor Nancy PollardPresenter Biography:
    Nancy Pollard is an Associate Professor in the Robotics Institute and Computer Science Department at Carnegie Mellon University.
    She received her PhD in Electrical Engineering and Computer Science from the MIT Artificial Intelligence Laboratory in 1994, where she performed research on grasp planning for articulated robot hands. Before joining CMU, Nancy was an Assistant Professor and part of the Computer Graphics Group at Brown University. She received the NSF CAREER award in 2001 for research on 'Quantifying Humanlike Enveloping Grasps' and the Okawa Research Grant in 2006 for "Studies of Dexterity for Computer Graphics and Robotics."Abstract:
    Data captured from human performances of activities ranging from the everyday through the extraordinary has become widely accessible over the past 10 years. The ability to download or capture human motion and process it in real-time has led to many new algorithms and new ways of thinking about character animation and robot control. However, we do not yet know how to make the most effective use of this data. What is important about a given performance? How can it be modified to create realistic new scenarios? And what are the limits of this approach. Can we ever create behavior that could be called dexterous from a collection of observed performances?In this talk, I will focus on the problem of creating dexterous grasping and manipulation behaviors from observed performances. I will discuss how my ideas have changed over the past decade, as we have gone from the idea that a grasp is made up of contact points between the hand and object through consideration of the hand geometry, anatomical constraints, and dynamic properties to the observation that grasps often involve preparatory sensing and manipulation actions which we have shown can reduce the effort needed to acquire an object. Results in computer animation and robot control, as well as results from controlled human subjects experiments will be presented.

    Location: UPC: GFS 220

    Audiences: Everyone Is Invited

    Contact: Toyicha Chisom

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  • CS Colloq: Data-Driven Grasping and Manipulation

    Tue, Feb 26, 2008 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Title: Data-Driven Grasping and ManipulationSpeaker: Prof. Nancy Pollard (CMU)ABSTRACT:
    ata captured from human performances of activities ranging from the everyday
    through the extraordinary has become widely accessible over the past 10 years.
    The ability to download or capture human motion and process it in real-time
    has led to many new algorithms and new ways of thinking about character
    animation and robot control. However, we do not yet know how to make the most
    effective use of this data. What is important about a given performance? How
    can it be modified to create realistic new scenarios? And what are the limits
    of this approach. Can we ever create behavior that could be called dexterous
    from a collection of observed performances?In this talk, I will focus on the problem of creating dexterous grasping and
    manipulation behaviors from observed performances. I will discuss how my ideas
    have changed over the past decade, as we have gone from the idea that a grasp
    is made up of contact points between the hand and object through consideration
    of the hand geometry, anatomical constraints, and dynamic properties to the
    observation that grasps often involve preparatory sensing and manipulation
    actions which we have shown can reduce the effort needed to acquire an object.
    Results in computer animation and robot control, as well as results from
    controlled human subjects experiments will be presented.BIO:
    Nancy Pollard is an Associate Professor in the Robotics Institute and Computer
    Science Department at Carnegie Mellon University. She received her PhD in
    Electrical Engineering and Computer Science from the MIT Artificial
    Intelligence Laboratory in 1994, where she performed research on grasp
    planning for articulated robot hands. Before joining CMU, Nancy was an
    Assistant Professor and part of the Computer Graphics Group at Brown
    University. She received the NSF CAREER award in 2001 for research on
    'Quantifying Humanlike Enveloping Grasps' and the Okawa Research Grant in 2006
    for "Studies of Dexterity for Computer Graphics and Robotics."

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 220

    Audiences: Everyone Is Invited

    Contact: CS Colloquia

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  • CS Colloq: Apprenticeship Learning

    Tue, Feb 26, 2008 @ 03:30 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Title: Apprenticeship LearningSpeaker: Pieter Abbeel (Stanford)ABSTRACT:
    Machine learning is a powerful paradigm which enables autonomous
    decision making by learning from examples. Despite its successes,
    human learning and decision making still vastly outperform autonomous
    decision making, particularly for complex sequential decision making
    tasks, where decisions made now have great ramifications far into the
    future. In this talk, I will present machine learning techniques with
    formal performance guarantees that efficiently learn to perform well
    in the apprenticeship learning setting---the setting when expert
    demonstrations of the (sequential decision making) task are available.
    I will also describe how my apprenticeship learning techniques have
    enabled us to solve real-world problems that could not be solved
    before. For example, they have enabled a helicopter to perform by far
    the most challenging aerobatic maneuvers performed by any autonomous
    helicopter to date. They have also enabled us to learn an autonomous
    controller for a quadruped robot to traverse challenging terrains and
    to learn a variety of different driving behaviours in our highway
    driving simulator.BIO:
    Pieter Abbeel is a Ph.D. candidate in the Computer Science
    Department at Stanford University. His research focuses on machine
    learning, including both the foundations of learning, and its practical
    application to problems in text mining, computer vision, control,
    computational biology, graphics, and computer systems.

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Contact: CS Colloquia

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  • VSC General Meeting

    Tue, Feb 26, 2008 @ 04:00 PM - 05:00 PM

    Viterbi School of Engineering Student Organizations

    Student Activity


    This is the fourth general meeting of the semester. We will be recapping the events of E-Week as well as discussing upcoming plans for the rest of the semester.

    Location: Norman Topping Student Activities Center (TSC) - 205

    Audiences: Everyone Is Invited

    Contact: VSC

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  • Alcon Information Session

    Tue, Feb 26, 2008 @ 06:00 PM - 07:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Join representatives of this company as they share general company information and available opportunities.

    Location: Grace Ford Salvatori (GFS) 106

    Audiences: All Viterbi Students

    Contact: RTH 218 Viterbi Career Services

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