TRAIL Team Description Paper for RoboCup@Home 2023
Our team, TRAIL, consists of AI/ML laboratory members from The University of Tokyo. We leverage our extensive research experience in state-of-the-art machine learning to build general-purpose in-home service robots. We previously participated in two competitions using Human Support Robot (HSR): Robo...
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Zusammenfassung: | Our team, TRAIL, consists of AI/ML laboratory members from The University of
Tokyo. We leverage our extensive research experience in state-of-the-art
machine learning to build general-purpose in-home service robots. We previously
participated in two competitions using Human Support Robot (HSR): RoboCup@Home
Japan Open 2020 (DSPL) and World Robot Summit 2020, equivalent to RoboCup World
Tournament. Throughout the competitions, we showed that a data-driven approach
is effective for performing in-home tasks. Aiming for further development of
building a versatile and fast-adaptable system, in RoboCup @Home 2023, we unify
three technologies that have recently been evaluated as components in the
fields of deep learning and robot learning into a real household robot system.
In addition, to stimulate research all over the RoboCup@Home community, we
build a platform that manages data collected from each site belonging to the
community around the world, taking advantage of the characteristics of the
community. |
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DOI: | 10.48550/arxiv.2310.03913 |