•   When: Friday, March 04, 2022 from 11:00 AM to 12:00 PM
•   Speakers: Jeffrey Ichnowski
•   Location: ZOOM only
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Abstract:

Robots in unstructured environments manipulate objects slowly and intermittently, relying on bursts of computation for planning. This is in stark contrast to humans who routinely use dynamic motions--such as vaulting power cords over chairs when vacuuming, flinging garments to flatten before folding, and lofting sheets across beds. Dynamic motions can speed task completion, manipulate objects out of reach, and increase reliability, but they require: (1) integrating grasp planning, motion planning, and time-parameterization, (2) lifting quasi-static assumptions, and (3) intermittent access to powerful computing. I will describe how recent advances in deep learning, optimization, and cloud robotics can meet these requirements, setting the stage for an exciting new chapter in dynamic robot manipulation.   

Bio:

Jeffrey Ichnowski is a post-doctoral researcher in the RISE lab and AUTOLAB at the University of California at Berkeley. He researches algorithms and systems for high-speed motion, task, and grasp planning for robots, using cloud-based high-performance computing, optimization, and deep learning. Jeff has a Ph.D. in computational robotics from the University of North Carolina at Chapel Hill. Before returning to academia, he founded startups and was an engineering director and the principal architect at SuccessFactors, one of the world’s largest cloud-based software-as-a-service companies.