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Events for December

  • PhD Defense - Nicholas Rotella

    Tue, Dec 05, 2017 @ 02:00 PM - 04:00 PM

    Computer Science

    University Calendar


    Tuesday, December 5th, 2 p.m. to 4 p.m, RTH 406

    PhD Candidate: Nicholas Rotella

    Title: Estimation-based control for humanoid robots

    Abstract:
    As sensor, actuator and processor technology continues to improve, humanoid robots have become more common in both academic and industrial environments. These robots have the potential to operate in complex environments built for humans given their form factor. However, the challenge of operating autonomously in unknown environments involves obtaining accurate estimates of the robot's state by fusing information from on-board sensors, and using these estimates for control in ways which allow robustness to uncertainty and disturbances. In this work, we propose methods for estimating important states of humanoid robots and evaluate the role of sensory information and state estimation in executing behaviors on a torque-controlled humanoid.

    Committee:
    Stefan Schaal
    Ludovic Righetti
    Laurent Itti
    James Finley

    Location: 406

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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  • PhD Defense - James Tanner

    Thu, Dec 07, 2017 @ 02:00 PM - 04:00 PM

    Computer Science

    University Calendar


    PhD Candidate: James Tanner

    Chair: Laurent Itti
    Irving Biederman
    Nora Ayanian


    Understanding the Relationship Between Goals and Attention

    It is well-known that tasks have a large influence on human gaze, and there exist many saliency models that incorporate some form of top-down features. However, these are all learned features, and little research has gone into quantifying the effects of task on eye movement behavior in a way that can predict those effects a priori. First, we demonstrate a new learning rule that suggests how top-down connections might operate in the brain, from a functional perspective. Then, we propose a quantitative theory for measuring the relevance of information with respect to tasks. Finally, we perform an experiment to further validate this theory and utilize it to improve a saliency model.

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 109

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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