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A typical assumption in state-of-the-art self-localization models is that an annotated training dataset is available in the target workspace. However, this does not always hold when a robot travels in a general open-world. This study introduces a nov
Externí odkaz:
http://arxiv.org/abs/2403.10552
Autor:
Tsukahara, Kenta, Tanaka, Kanji
A typical assumption in state-of-the-art self-localization models is that an annotated training dataset is available for the target workspace. However, this is not necessarily true when a robot travels around the general open world. This work introdu
Externí odkaz:
http://arxiv.org/abs/2312.15897
Visual place classification from a first-person-view monocular RGB image is a fundamental problem in long-term robot navigation. A difficulty arises from the fact that RGB image classifiers are often vulnerable to spatial and appearance changes and d
Externí odkaz:
http://arxiv.org/abs/2305.06179
Akademický článek
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Autor:
Tsukahara, Kenta, Kondo, Keiichiro
Publikováno v:
IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society; 2013, p4534-4539, 6p