Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Pascal Meissner"'
Autor:
Pascal Meißner, Rüdiger Dillmann
Publikováno v:
Robotics, Vol 12, Iss 6, p 158 (2023)
This article describes an approach for mobile robots to identify scenes in configurations of objects spread across dense environments. This identification is enabled by intertwining the robotic object search and the scene recognition on already detec
Externí odkaz:
https://doaj.org/article/7a3986d0267b4b5f930ad1627601adb6
Publikováno v:
IEEE Robotics and Automation Letters. 5:4828-4835
Flexible pick-and-place is a fundamental yet challenging task within robotics, in particular due to the need of an object model for a simple target pose definition. In this work, the robot instead learns to pick-and-place objects using planar manipul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c2b98dcb087e58f027ead9435dc58c2
https://doi.org/10.1109/lra.2020.3003865
https://doi.org/10.1109/lra.2020.3003865
Publikováno v:
University of Aberdeen-PURE
Robot learning of real-world manipulation tasks remains challenging and time consuming, even though actions are often simplified by single-step manipulation primitives. In order to compensate the removed time dependency, we additionally learn an imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ef5ccd58455de213d57fbdc5af6f6d6
https://doi.org/10.1109/iros51168.2021.9636623
https://doi.org/10.1109/iros51168.2021.9636623
Publikováno v:
IROS
We present TrueAEdapt, a model-free method to learn online adaptations of robot trajectories based on their effects on the environment. Given sensory feedback and future waypoints of the original trajectory, a neural network is trained to predict joi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0dc61308cfa592a837c9a773d05b164
https://doi.org/10.1109/iros45743.2020.9341001
https://doi.org/10.1109/iros45743.2020.9341001
Publikováno v:
ICRA
We present TrueRMA, a data-efficient, model-free method to learn cost-optimized robot trajectories over a wide range of starting points and endpoints. The key idea is to calculate trajectory waypoints in Cartesian space by recursively predicting orth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c2a3dfb265b1c91285758ebe762e4ce
http://arxiv.org/abs/2006.03497
http://arxiv.org/abs/2006.03497
Autor:
Pascal Meißner
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783030318512
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::961366a47f11ad3fec95bcac10b2cb27
https://doi.org/10.1007/978-3-030-31852-9
https://doi.org/10.1007/978-3-030-31852-9
Autor:
Pascal Meißner
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783030318512
Detailed technical presentation of our contributions that are related to Passive Scene Recognition. This includes the learning of Trees of Implicit Shape Models as well as carrying out scene recognition on the basis of these classifiers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fff8714e3fe98e6ca6dc3e96e6f44ce8
https://doi.org/10.1007/978-3-030-31852-9_3
https://doi.org/10.1007/978-3-030-31852-9_3
Autor:
Pascal Meißner
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783030318512
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::297087e6fd39ab82bbc8cc268bf5e1a0
https://doi.org/10.1007/978-3-030-31852-9_5
https://doi.org/10.1007/978-3-030-31852-9_5
Autor:
Pascal Meißner
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783030318512
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d1125b2d06a53a55877927a32a272b2
https://doi.org/10.1007/978-3-030-31852-9_1
https://doi.org/10.1007/978-3-030-31852-9_1
Autor:
Pascal Meißner
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783030318512
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5dc1319636194dffe5afc6e2aea5eb6
https://doi.org/10.1007/978-3-030-31852-9_2
https://doi.org/10.1007/978-3-030-31852-9_2