
Designing Robot Behavior in Human-Robot Interactions
Description
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Key Features:
Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions.
Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications.
Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.
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Persons
Te Tang received his PhD degree from University of California at Berkeley in 2018. He joined FANUC America Corporation in 2018, and he is currently a researcher at FANUC Advanced Research Laboratory. His research interests include robotics, learning from demonstration, computer vision and their industrial applications.
Hsien-Chung Lin is a research engineer in FANUC Advanced Research Laboratory at FANUC America Corporation. Prior to joining FANUC, he received his Ph.D. degree from University of California at Berkeley in 2018. His research interests cover robotics, optimal control, human-robot interaction, learning from demonstration and motion planning.
Masayoshi Tomizuka received his PhD degree from MIT in 1974. In 1974, he joined the Mechanical Engineering Department of the University of California, Berkeley, where he currently is Cheryl and John Neerhout, Jr., Distinguished Professor. His research interests are control theory and its applications to mechatronic systems such as robots. He is a Life Fellow of ASME and IEEE, and a Fellow of IFAC. He was awarded the Rufus Oldenburger Medal (2002) and the Richard Bellman Control Heritage Award (2018).
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