Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Fernando Cladera Ojeda"'
Autor:
Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler
Publikováno v:
IEEE Robotics and Automation Letters. 7:8737-8744
Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal tools for r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23f5e9d829e2c3d108f4db8069cd82e2
https://doi.org/10.1109/lra.2022.3188400
https://doi.org/10.1109/lra.2022.3188400
Autor:
Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda, Yuezhan Tao, Alex Zhou, Thomas Donnelly, Chao Qu, Steven W. Chen, Roseli A. F. Romero, Camillo J. Taylor, Vijay Kumar
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilitating large-scale autonomy and the acquisition of actionable informati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82f954f4bcfbdd895a0b6fcdfa8bb3d8
https://doi.org/10.1109/lra.2022.3154047
https://doi.org/10.1109/lra.2022.3154047
Autor:
Xu Liu, Steven W. Chen, Guilherme V. Nardari, Chao Qu, Fernando Cladera Ojeda, Camillo J. Taylor, Vijay Kumar
Publikováno v:
IEEE Micro. 42:61-68
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2261b112fc2d5e77188b06d50f642a9a
https://doi.org/10.1109/mm.2021.3134744
https://doi.org/10.1109/mm.2021.3134744
Autor:
Alice K. Li, Yue Mao, Sandeep Manjanna, Sixuan Liu, Jasleen Dhanoa, Bharg Mehta, Victoria M. Edwards, Fernando Cladera Ojeda, M. Ani Hsieh, Maël Le Men, Eric Sigg, Douglas J. Jerolmack, Hugo N. Ulloa
Publikováno v:
OCEANS 2022, Hampton Roads.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07107ca3cd18dd2d1f73f2ce304c9470
https://doi.org/10.1109/oceans47191.2022.9977236
https://doi.org/10.1109/oceans47191.2022.9977236
Publikováno v:
ICRA
This paper presents a Dynamic Vision Sensor (DVS) based system for reasoning about high speed motion. As a representative scenario, we consider the case of a robot at rest reacting to a small, fast approaching object at speeds higher than 15m/s. Sinc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::643c563ee5c9481a75c0ce3ea4706af0
https://doi.org/10.1109/icra48506.2021.9561290
https://doi.org/10.1109/icra48506.2021.9561290
Publikováno v:
ICIP
In this work, we present a hardware-efficient architecture for pedestrian detection with neuromorphic Dynamic Vision Sensors (DVSs), asynchronous camera sensors that report discrete changes in light intensity. These imaging sensors have many advantag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76fa78463f05ea1de8f7826a4f2aa7f0
https://doi.org/10.1109/icip40778.2020.9191148
https://doi.org/10.1109/icip40778.2020.9191148
Publikováno v:
ISVLSI
This paper presents a novel end-to-end system for pedestrian detection using Dynamic Vision Sensors (DVSs). We target applications where multiple sensors transmit data to a local processing unit, which executes a detection algorithm. Our system is co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94673796966a04810e4bc1e9a4f935f9
