Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Yasemin Bekiroglu"'
Autor:
Yasemin Bekiroglu, Mårten Björkman, Gabriela Zarzar Gandler, Johannes Exner, Carl Henrik Ek, Danica Kragic
Publikováno v:
Data in Brief, Vol 30, Iss , Pp 105335- (2020)
Representing 3D geometry for different tasks, e.g. rendering and reconstruction, is an important goal in different fields, such as computer graphics, computer vision and robotics. Robotic applications often require perception of object shape informat
Externí odkaz:
https://doaj.org/article/5d1df00637434e559c9d7d57bd991bcf
Autor:
Florian T. Pokorny, Yasemin Bekiroglu, Karl Pauwels, Judith Butepage, Clara Scherer, Danica Kragic
Publikováno v:
Data in Brief, Vol 11, Iss C, Pp 491-498 (2017)
We present a novel approach and database which combines the inexpensive generation of 3D object models via monocular or RGB-D camera images with 3D printing and a state of the art object tracking algorithm. Unlike recent efforts towards the creation
Externí odkaz:
https://doaj.org/article/e1286bd2fb22455995734d93e411bb5d
Publikováno v:
IEEE Robotics and Automation Letters. 7:11759-11766
Publikováno v:
IEEE Robotics and Automation Letters. 6:3349-3356
This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement to optimise grasp stability. In many situations, a robot will have only
Autor:
Nishad Gothoskar, Miguel Lazaro-Gredilla, Yasemin Bekiroglu, Abhishek Agarwal, Joshua B. Tenenbaum, Vikash K. Mansinghka, Dileep George
Visual servoing enables robotic systems to perform accurate closed-loop control, which is required in many applications. However, existing methods either require precise calibration of the robot kinematic model and cameras or use neural architectures
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28b6f09467b9dee6c1b27dfc333cc528
Autor:
Tommaso Pardi, Cindy Grimm, Kaiyu Hang, Yasemin Bekiroglu, Ravi Balasubramanian, Komlan Jean Maxime Adjigble, Naresh Marturi, Maximo A. Roa, Rustam Stolkin
Numerous grasp planning algorithms have been proposed since the 1980s. The grasping literature has expanded rapidly in recent years, building on greatly improved vision systems and computing power. Methods have been proposed to plan stable grasps on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10eb8928584f1ee0d99129d6865fbb8b
https://elib.dlr.de/136150/
https://elib.dlr.de/136150/
Autor:
Robert Haschke, Joseph McIntyre, Jacek Malec, Yasemin Bekiroglu, Ioannis Mariolis, Yiannis Karayiannidis, Anthony Remazeilles
Publikováno v:
Impact. 2017:67-69
Publikováno v:
Robotics and Autonomous Systems. 126:103433
Inferring and representing three-dimensional shapes is an important part of robotic perception. However, it is challenging to build accurate models of novel objects based on real sensory data, because observed data is typically incomplete and noisy.
Publikováno v:
ICRA
Assessing grasp quality and, subsequently, predicting grasp success is useful for avoiding failures in many autonomous robotic applications. In addition, interest in nonprehensile grasping and manipulation has been growing as it offers the potential
Publikováno v:
IROS
In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::535aaf2fbc72f7c1bdcaf6cdbe78af33