Zobrazeno 1 - 10
of 111
pro vyhledávání: '"François Pomerleau"'
Publikováno v:
SN Applied Sciences, Vol 3, Iss 5, Pp 1-14 (2021)
Abstract We present a generalized mapping framework that can withstand the challenges incurred by working in unstructured outdoor environments, such as a snowy forest. The proposed method takes advantage of a sensor fusion scheme, where sensors such
Externí odkaz:
https://doaj.org/article/d908fb33e3d245d7919a52de71b5333a
Publikováno v:
Frontiers in Robotics and AI, Vol 7 (2020)
In the context of 3D mapping, larger and larger point clouds are acquired with lidar sensors. Although pleasing to the eye, dense maps are not necessarily tailored for practical applications. For instance, in a surface inspection scenario, keeping ge
Externí odkaz:
https://doaj.org/article/391cdcb703464cda9ce87cceafeb7a96
Autor:
Johann Laconte, Abderrahim Kasmi, François Pomerleau, Roland Chapuis, Laurent Malaterre, Christophe Debain, Romuald Aufrère
Publikováno v:
Sensors, Vol 21, Iss 22, p 7562 (2021)
In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probabil
Externí odkaz:
https://doaj.org/article/79a66134c342462ab70ac04696c92dcb
Publikováno v:
Towards Human-Vehicle Harmonization ISBN: 9783110981223
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f75a98c794de42cee51af543d6a81cd
https://doi.org/10.1515/9783110981223-018
https://doi.org/10.1515/9783110981223-018
Autor:
François Pomerleau
Publikováno v:
Encyclopedia of Robotics ISBN: 9783642416101
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6655e13aebd99689e8a3bb845dc0c49
https://doi.org/10.1007/978-3-642-41610-1_223-1
https://doi.org/10.1007/978-3-642-41610-1_223-1
Publikováno v:
SN Applied Sciences, Vol 3, Iss 5, Pp 1-14 (2021)
SN Applied Sciences
SN Applied Sciences, Springer Verlag, 2021, 3 (5), ⟨10.1007/s42452-021-04555-y⟩
SN Applied Sciences
SN Applied Sciences, Springer Verlag, 2021, 3 (5), ⟨10.1007/s42452-021-04555-y⟩
We present a generalized mapping framework that can withstand the challenges incurred by working in unstructured outdoor environments, such as a snowy forest. The proposed method takes advantage of a sensor fusion scheme, where sensors such as camera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ae84972b27bd21de29f7ad7aedf8980
https://doaj.org/article/d908fb33e3d245d7919a52de71b5333a
https://doaj.org/article/d908fb33e3d245d7919a52de71b5333a
Publikováno v:
Journal of Field Robotics. 37:1347-1362
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf8740d71bba0c81e1bfb6cdfe55fa83
https://doi.org/10.1002/rob.21988
https://doi.org/10.1002/rob.21988
Publikováno v:
Journal of Field Robotics. 37:1328-1346
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1dd70eeff13cd3ff7d6739877172b7a
https://doi.org/10.1002/rob.21980
https://doi.org/10.1002/rob.21980
Tree perception is an essential building block toward autonomous forestry operations. Current developments generally consider input data from lidar sensors to solve forest navigation, tree detection and diameter estimation problems, whereas cameras p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba5189f23e77dd4fbf11b94e1cc4ef73
Autor:
Simon-Pierre Deschênes, Vladimír Kubelka, Philippe Giguère, Dominic Baril, François Pomerleau
Publikováno v:
CRV
Registration algorithms, such as Iterative Closest Point (ICP), have proven effective in mobile robot localization algorithms over the last decades. However, they are susceptible to failure when a robot sustains extreme velocities and accelerations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3026fc4a16eba4d3b2dd9abaea531e1
http://arxiv.org/abs/2105.01215
http://arxiv.org/abs/2105.01215