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  • CS Colloquium: Masahiro Ono (NASA JPL) - Robots in Space: How AI and Machine Learning are Revolutionizing Space Exploration

    Thu, Oct 31, 2019 @ 02:00 PM - 03:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Masahiro Ono, NASA JPL

    Talk Title: Robots in Space: How AI and Machine Learning are Revolutionizing Space Exploration

    Series: Computer Science Colloquium

    Abstract: On the third planet of the Solar System, there is an ongoing revolution caused by a group of technologies collectively called as \"AI,\" including, but not limited to, machine learning, optimal decision making, situation awareness, and autonomous navigation. The same revolution is taking off elsewhere in the Solar System, triggered by an advent of HPSC (high-performance spacecraft computing). This talk introduces ongoing research efforts to adapt and enhance latest AI technologies for future exploration missions to Mars, Europa, and Enceladus, such as resource-aware autonomous rover driving, on-board science interpretation, and autonomous descent into Enceladus\'s vents, which are believed to be connected to the subsurface ocean that may harbor extraterrestrial life.

    If you would like to take a peek of the talk, take a look at the following YouTube movies:

    This lecture satisfies requirements for CSCI 591: Research Colloquium. *Note: Rescheduled to 10/31/19, 2:00-3:20PM*

    Biography: Dr. Masahiro (Hiro) Ono is a Research Technologist at NASA Jet Propulsion Laboratory, California Institute of Technology. His broad interest is centered around the application of robotic autonomy to space exploration, with an emphasis on machine learning applications to perception, data interpretation, and decision making. Before joining JPL in 2013, he was an assistant professor at Keio University in Japan. He graduated from MIT with PhD in Aeronautics and Astronautics in 2012. Since 2017 he is the PI of a JPL-funded Strategic Research and Development task on the machine learning-based analytics for automated rover systems (MAARS). From 2015 he has led the development of machine learning- based Martian terrain classifier, which is used by MSL and Mars 2020 Rover missions. He was also the PI of a JPL-Caltech joint project on imitation learning-based planning from 2016 to 2018. He was awarded two NIAC Phase I studies: Comet Hitchhiker (2014) and Journey to the Center of Icy Moon (2016). Since 2019, he has been the Autonomy Lead of the EELS (Exobiology Extant Life Surveyor) project.

    Host: Stefanos Nikolaidis

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department


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