Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Kai Huebner"'
Autor:
Kai Huebner
Publikováno v:
Robotics and Autonomous Systems. 60:367-376
In this paper, we conclude our work on shape approximation by box primitives for the goal of simple and efficient grasping. As a main product of our research, we present the BADGr toolbox for Box-based Approximation, Decomposition and Grasping of obj
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::947e0c33b657b393c4bd0f5fb6769e28
https://doi.org/10.1016/j.robot.2011.07.021
https://doi.org/10.1016/j.robot.2011.07.021
Autor:
Dan Song, Danica Kragic, Jeannette Bohg, Maria Ralph, Kai Huebner, Carl Barck-Holst, Babak Rasolzadeh
Publikováno v:
International Journal of Humanoid Robotics. :387-434
A distinct property of robot vision systems is that they are embodied. Visual information is extracted for the purpose of moving in and interacting with the environment. Thus, different types of perception-action cycles need to be implemented and eva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9124175a54dc79bbf054a257885d6214
https://doi.org/10.1142/s0219843609001796
https://doi.org/10.1142/s0219843609001796
Publikováno v:
International Journal of Information Acquisition. :241-249
In [Westhoff et al., 2005], we proposed a novel method to determine illumination-invariant features in images. The quantitative bilateral symmetry of a given scene is computed using dynamic programming before applying the resulting symmetry image and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45735498e782d6ee829915289f513e1c
https://doi.org/10.1142/s021987890500060x
https://doi.org/10.1142/s021987890500060x
Publikováno v:
IROS
University of Bristol-PURE
University of Bristol-PURE
We study embodiment-specific robot grasping tasks, represented in a probabilistic framework. The framework consists of a Bayesian network (BN) integrated with a novel multi-variate discretization model. The BN models the probabilistic relationships a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41497215471279d282a18a388d1c471c
https://doi.org/10.1109/iros.2011.6094503
https://doi.org/10.1109/iros.2011.6094503
Publikováno v:
ICRA
This paper presents an integration of grasp planning and online grasp stability assessment based on tactile data. We show how the uncertainty in grasp execution posterior to grasp planning can be dealt with using tactile sensing and machine learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9507c2f70584edf34f5a53bb9438d1fd
https://doi.org/10.1109/icra.2011.5980049
https://doi.org/10.1109/icra.2011.5980049
Publikováno v:
Humanoids
University of Bristol-PURE
University of Bristol-PURE
An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2150cf0bcdc906d85cada2db77457d9
https://doi.org/10.1109/ichr.2010.5686348
https://doi.org/10.1109/ichr.2010.5686348
Publikováno v:
IROS
We study two important problems in the area of robot grasping: i) the methodology and representations for grasp selection on known and unknown objects, and ii) learning from experience for grasping of similar objects. The core part of the paper is th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7385b49007c069981d0b0c5815b8fca8
https://doi.org/10.1109/iros.2010.5648993
https://doi.org/10.1109/iros.2010.5648993
Publikováno v:
IROS
This paper studies the learning of task constraints that allow grasp generation in a goal-directed manner. We show how an object representation and a grasp generated on it can be integrated with the task requirements. The scientific problems tackled
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd2e548be2ce782706846f2102545a59
https://doi.org/10.1109/iros.2010.5649406
https://doi.org/10.1109/iros.2010.5649406
The ability to autonomously acquire new knowledge through interaction with the environment is an important research topic in the field of robotics. The knowledge can only be acquired if suitable perception— action capabilities are present: a roboti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b5d6b71efeb08504cb01681b93b85af
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-28720
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-28720
Publikováno v:
Robotics: Science and Systems
In this paper, we bridge and extend the approaches of 3D shape approximation and 2D grasping strategies. We begin by applying a shape decomposition to an object, i.e. its extracted 3D point data, u ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7964a9fff8ac2c4f3ac5d9fc33f3d261
https://doi.org/10.15607/rss.2009.v.002
https://doi.org/10.15607/rss.2009.v.002