Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ana Lucia Pais Ureche"'
Autor:
Michael Beetz, Alexis Maldonado, Aude Billard, Andrei Haidu, Daniel Bebler, Hagen Langer, Ana Lucia Pais Ureche, Jan-Hendrik Worch, Thiemo Wiedemeyer, Zhou Fang, Asil Kaan Bozcuoglu, Moritz Tenorth, Ferenc Balint-Benczedi, Jan Winkler, Georg Bartels, Nadia Figueroa
Publikováno v:
ICRA
In this paper we discuss how the combination of modern technologies in “big data” storage and management, knowledge representation and processing, cloud-based computation, and web technology can help the robotics community to establish and streng
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f858d68af0cdd812bdac0d794833e52c
https://doi.org/10.1109/icra.2016.7487749
https://doi.org/10.1109/icra.2016.7487749
Autor:
Aude Billard, Ana Lucia Pais Ureche
Publikováno v:
HRI (Extended Abstracts)
In robot Programming by Demonstration (PbD), the interaction with the human user is key to collecting good demonstrations, learning and finally achieving a good task execution. We therefore take a dual approach in analyzing demonstration data. First
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99eaa60a7deb0869554951a5d6215b01
https://doi.org/10.1145/2701973.2702731
https://doi.org/10.1145/2701973.2702731
Autor:
Ana-Lucia Pais Ureche, Aude Billard
Publikováno v:
HRI (Extended Abstracts)
One of the major challenges in Programming by Demonstration is deciding who to imitate. In this paper we propose a set of metrics for assessing how skilled a user is when demonstrating a bimanual task to a robot, that requires both a coordinated moti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87a085901019af7b084bc2db0bddce17
https://doi.org/10.1145/2701973.2702017
https://doi.org/10.1145/2701973.2702017
Autor:
Ana-Lucia Pais Ureche, Aude Billard
Publikováno v:
HRI (Extended Abstracts)
In robot programming by demonstration dealing with high dimensional data that comes from human demonstrations is often subject to embedding prior knowledge of which variables should be retained and why. This paper proposes an approach for automatizin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05f3bd29619720eb26e6807f7d3703d3
https://doi.org/10.1145/2701973.2702007
https://doi.org/10.1145/2701973.2702007
In this paper, we propose an approach for learning task specifications automatically, by observing human demonstrations. Using this approach allows a robot to combine representations of individual actions to achieve a high-level goal. We hypothesize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d506ba7fc0402d8abfa82daa7006c0b
https://infoscience.epfl.ch/record/216892
https://infoscience.epfl.ch/record/216892
This paper introduces a hierarchical framework that is capable of learning complex sequential tasks from human demonstrations through kinesthetic teaching, with minimal human intervention. Via an automatic task segmentation and action primitive disco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97e2158076017abcdf030acc423f6744
https://infoscience.epfl.ch/record/221954
https://infoscience.epfl.ch/record/221954