Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Tchuiev, Vladimir"'
Training neural networks is computationally heavy and energy-intensive. Many methodologies were developed to save computational requirements and energy by reducing the precision of network weights at inference time and introducing techniques such as
Externí odkaz:
http://arxiv.org/abs/2410.09734
Autor:
Joglekar, Omkar, Lancewicki, Tal, Kozlovsky, Shir, Tchuiev, Vladimir, Feldman, Zohar, Di Castro, Dotan
Large Language Models (LLMs) and strong vision models have enabled rapid research and development in the field of Vision-Language-Action models that enable robotic control. The main objective of these methods is to develop a generalist policy that ca
Externí odkaz:
http://arxiv.org/abs/2406.16093
Object manipulation in cluttered scenes is a difficult and important problem in robotics. To efficiently manipulate objects, it is crucial to understand their surroundings, especially in cases where multiple objects are stacked one on top of the othe
Externí odkaz:
http://arxiv.org/abs/2207.09105
We address the problem of devising the means for a robot to rapidly and safely learn insertion skills with just a few human interventions and without hand-crafted rewards or demonstrations. Our InsertionNet version 2.0 provides an improved technique
Externí odkaz:
http://arxiv.org/abs/2203.01153
Autor:
Tchuiev, Vladimir, Indelman, Vadim
We investigate the problem of autonomous object classification and semantic SLAM, which in general exhibits a tight coupling between classification, metric SLAM and planning under uncertainty. We contribute a unified framework for inference and belie
Externí odkaz:
http://arxiv.org/abs/2105.12359
Autor:
Tchuiev, Vladimir, Indelman, Vadim
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 5 , Issue: 3 , July 2020 ) pp. 4649 - 4656
We present an approach for multi-robot consistent distributed localization and semantic mapping in an unknown environment, considering scenarios with classification ambiguity, where objects' visual appearance generally varies with viewpoint. Our appr
Externí odkaz:
http://arxiv.org/abs/2007.02611
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.