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Robust Perception for Simultaneous Localization and Mapping in Extreme Environments

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Abstract: Common sensor choices in Simultaneous Localization and Mapping (SLAM) include sensors in the visible spectrum, such as cameras and lidars. In this talk, we will explore robust sensing through three approaches: firstly, by utilizing cameras to capture high-level features, we can improve perception by steering clear of less effective point-based methods. Secondly, by integrating learning-based techniques into Object SLAM , we can ensure reliable performance in robotic manipulation. Finally, we will explore alternative sensing capabilities beyond the visible spectrum, showcasing research involving radars and thermal cameras.

Bio: Prof. Ayoung Kim works as an Associate Professor in the Department of Mechanical Engineering at Seoul National University (SNU) since 2021 September, leading the Robust Perception and Mobile Robotics Lab. Before joining SNU , she was an Associate Professor at the Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST) from 2014 to 2021. She has an M.S. Degree in Electrical Engineering and a Ph.D. Degree in Mechanical Engineering from the University of Michigan (UM), Ann Arbor, in 2011 and 2012. She also worked as a post-doctoral researcher in naval architecture and marine engineering at UM in 2013 before she worked at Electronics and Telecommunications Research Institute (ETRI) as a senior researcher. She received the Korea Robotics Society Young Researcher Award in 2019 and serves as an Associate Editor for IEEE Transactions on Robotics, IEEE Robotics and Automation Letters, etc.

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