Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Luis Riazuelo"'
Autor:
Pablo Azagra, Carlos Sostres, Ángel Ferrández, Luis Riazuelo, Clara Tomasini, O. León Barbed, Javier Morlana, David Recasens, Víctor M. Batlle, Juan J. Gómez-Rodríguez, Richard Elvira, Julia López, Cristina Oriol, Javier Civera, Juan D. Tardós, Ana C. Murillo, Angel Lanas, José M. M. Montiel
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-16 (2023)
Abstract Computer-assisted systems are becoming broadly used in medicine. In endoscopy, most research focuses on the automatic detection of polyps or other pathologies, but localization and navigation of the endoscope are completely performed manuall
Externí odkaz:
https://doaj.org/article/fac3a3a3876f4fa0b4a6511e7bb1ff1a
Publikováno v:
Applied Sciences, Vol 13, Iss 15, p 8925 (2023)
Robotic autonomous navigation in dynamic environments is a complex problem, as traditional planners may fail to take dynamic obstacles and their variables into account. The Strategy-based Dynamic Object Velocity Space (S-DOVS) planner has been propos
Externí odkaz:
https://doaj.org/article/056ca67a1f6444e7b24a8793c7a24f7f
Publikováno v:
Sensors, Vol 22, Iss 10, p 3847 (2022)
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t
Externí odkaz:
https://doaj.org/article/854bf4c225384c98a32c3dc2a36a5ecc
Publikováno v:
ROBOT2022: Fifth Iberian Robotics Conference ISBN: 9783031210617
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::130c030153220be86ceed34aacbdffdd
https://doi.org/10.1007/978-3-031-21062-4_2
https://doi.org/10.1007/978-3-031-21062-4_2
Autor:
Kakia Panagidi, Luis Riazuelo, Iñigo Alonso, Ana C. Murillo, Luis Montano, Miquel Cantero, Ricardo Martins, Kostas Kolomvatsos, Stathes Hadjiefthymiades
Publikováno v:
ROBOT2022: Fifth Iberian Robotics Conference ISBN: 9783031210648
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26920fdda09ed4de2095b556dd666626
https://doi.org/10.1007/978-3-031-21065-5_13
https://doi.org/10.1007/978-3-031-21065-5_13
Publikováno v:
IEEE Robotics and Automation Letters. 5:5432-5439
LIDAR semantic segmentation, which assigns a semantic label to each 3D point measured by the LIDAR, is becoming an essential task for many robotic applications such as autonomous driving. Fast and efficient semantic segmentation methods are needed to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e2076aa628e87db13202f5703c26a76
https://doi.org/10.1109/lra.2020.3007440
https://doi.org/10.1109/lra.2020.3007440
Autor:
Luis Riazuelo, Luis Montano, Francisco Javier Rodríguez Lera, José Luis Villarroel, Domenico Sicignano, Carlos Rizzo, Danilo Tardioli
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
instname
The work reported in this article describes the research advances and the lessons learned by the Robotics, Perception and Real-Time group over a decade of research in the field of ground robotics in confined environments. This study has primarily foc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6652e783587ab3c21ab804bd112153b2
https://doi.org/10.1002/rob.21871
https://doi.org/10.1002/rob.21871
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
ICINCO
instname
ICINCO
LiDAR semantic segmentation provides 3D semantic information about the environment, an essential cue for intelligent systems during their decision making processes. Deep neural networks are achieving state-of-the-art results on large public benchmark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4128b8ab0619a539ad4af6212ff5f224
http://zaguan.unizar.es/record/108343
http://zaguan.unizar.es/record/108343
Publikováno v:
ICRA
Selecting relevant visual information from a video is a challenging task on its own and even more in robotics, due to strong computational restrictions. This work proposes a novel keyframe selection strategy based on image quality and semantic inform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec87582719f306b38aee8db13c62d04f
https://doi.org/10.1109/icra.2019.8793923
https://doi.org/10.1109/icra.2019.8793923