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Events for December 06, 2023

  • CS Colloquium: Oren Salzman (Technion - Israel Institute) - Towards Contact-Aided Motion Planning for Tendon-Driven Continuum Robots: A step-by-step tutorial of applying heuristic search in the wild.

    CS Colloquium: Oren Salzman (Technion - Israel Institute) - Towards Contact-Aided Motion Planning for Tendon-Driven Continuum Robots: A step-by-step tutorial of applying heuristic search in the wild.

    Wed, Dec 06, 2023 @ 09:30 AM - 10:30 AM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Oren Salzman, Technion - Israel Institute

    Talk Title: Towards Contact-Aided Motion Planning for Tendon-Driven Continuum Robots: A step-by-step tutorial of applying heuristic search in the wild.

    Abstract: Tendon-driven continuum robots (TDCRs), with their flexible backbones, offer the advantage of being used for navigating complex, cluttered environments. However, to do so, they typically require multiple segments, often leading to complex actuation and control challenges. To this end, we propose a novel approach to navigate cluttered spaces effectively for a single-segment long TDCR which is the simplest topology from a mechanical point of view. Our key insight is that by leveraging contact with the environment we can achieve multiple curvatures without mechanical alterations to the robot. Specifically, we propose a search-based motion planner for a single-segment TDCR. This planner, guided by a specially designed heuristic, discretizes the configuration space and employs a best-first search. In the talk I will cover the steps required to apply heuristic search to a complex robotic system; from kinematic modeling to heuristic computation. The talk assumes some background in heuristic search but requires no robotic background.The talk is based on joint work with Priyanka Rao and Jessica Burgner-Kars from UoT.
     
    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Oren Salzman is an assistant Professor at the Computer Science department at the Technion - Israel Instituteof Technology. His research focuses on revisiting classical computer science algorithms, tools and paradigms to address the computational challenges that arise when planning motions for robots. Combining techniques from diverse domains such as computational geometry, graph theory and machine learning, he strives to provide efficient algorithms with rigorous analysis for robot systems with many degrees of freedom moving in tight quarters. He completed a PhD in the School of Computer Science at Tel Aviv University under the supervision of Prof. Dan Halperin. He then continued his studies as a postdoctoral researcher at Carnegie Mellon University working with Siddhartha Srinivasa and Maxim Likhachev and as a research scientist at the National Robotics Engineering Center (NREC). Oren has published over sixty peer-reviewed conference and journal papers. He received the best paper and best student paper in ICAPS 18 and ICAPS 19, respectively as well as a nomination for the best-paper award at RSS 21.

    Host: Sven Koenig

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Contact: CS Events

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  • PhD Thesis Proposal - Nathan Bartley

    Wed, Dec 06, 2023 @ 12:00 PM - 01:30 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Proposal - Nathan Bartley Committee Members:
    Kristina Lerman (chair)
    Mike Ananny
    Emilio Ferrara
    red Morstatter
    Barath Raghavan
     
     Title: Content Exposure Bias and Online Social Networks
     
     Abstract: Online social platforms employ personalized feed algorithms to gather and collate messages from accounts users follow. However, the network structure and activity of the followed users distorts content’s perceived popularity prior to personalization. We call this “exposure bias:” our research focuses on quantifying it using diverse metrics, and we evaluate different algorithms that underpin personalized feeds with these metrics. We use empirical X/Twitter data and simulations in a network to assess the influence different feeds have on exposure bias. Furthermore we are working on agent-based model simulations to comprehend the impact of changing feeds, with the ultimate goal of making interventions. 
     
     

    Location: https://usc.zoom.us/j/98609708157?pwd=VWJuMVROL3Z5YVZmWDFWQ2xRRzNOUT09

    Audiences: Everyone Is Invited

    Contact: CS Events

    Event Link: https://usc.zoom.us/j/98609708157?pwd=VWJuMVROL3Z5YVZmWDFWQ2xRRzNOUT09

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