Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Lars Berscheid"'
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
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
Autor:
Lars Berscheid, Torsten Kroeger
Publikováno v:
Robotics: Science and Systems
We present Ruckig, an algorithm for Online Trajectory Generation (OTG) respecting third-order constraints and complete kinematic target states. Given any initial state of a system with multiple Degrees of Freedom (DoFs), Ruckig calculates a time-opti
Publikováno v:
ICRA
Robot learning is often simplified to planar manipulation due to its data consumption. Then, a common approach is to use a fully-convolutional neural network to estimate the reward of grasp primitives. In this work, we extend this approach by paramet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a77eca4e1e3c41957a86c050bad50cd8
http://arxiv.org/abs/2103.12810
http://arxiv.org/abs/2103.12810
Publikováno v:
IROS
Robotic grasping in cluttered environments is often infeasible due to obstacles preventing possible grasps. Then, pre-grasping manipulation like shifting or pushing an object becomes necessary. We developed an algorithm that can learn, in addition to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97ed9c7cdd1daa30408543a782fd0850
http://arxiv.org/abs/1907.11035
http://arxiv.org/abs/1907.11035
Publikováno v:
ICRA
Given the task of learning robotic grasping solely based on a depth camera input and gripper force feedback, we derive a learning algorithm from an applied point of view to significantly reduce the amount of required training data. Major improvements
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2cc858d262aeb6fd8c8129b56dd77ae
http://arxiv.org/abs/1903.00228
http://arxiv.org/abs/1903.00228
A Generic Approach to Self-localization and Mapping of Mobile Robots Without Using a Kinematic Model
Publikováno v:
Towards Autonomous Robotic Systems ISBN: 9783319224152
TAROS
TAROS
In this paper a generic approach to the SLAM (Simultaneous Localization and Mapping) problem is proposed. The approach is based on a probabilistic SLAM algorithm and employs only two portable sensors, an inertial measurement unit (IMU) and a laser ra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d9481ea03b7cd77f262dd4cb60b3eec
https://doi.org/10.1007/978-3-319-22416-9_15
https://doi.org/10.1007/978-3-319-22416-9_15
High power pulsed magnetron sputtering (HPPMS) plasmas are pulsed discharges where the plasma composition as well as the fluxes and energies of ions are changing during the pulse. The time resolved energy distribution for Ar$^{1+}$ ions was measured
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8198468274b158d77bc37a70e526fb3
Publikováno v:
Scopus-Elsevier
VISIGRAPP (5: VISAPP)
VISIGRAPP (5: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a00e13bf08325d74b9eb599108d63189
http://www.scopus.com/inward/record.url?eid=2-s2.0-85047818163&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85047818163&partnerID=MN8TOARS