Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Katrin Pirker"'
Publikováno v:
ICCV Workshops
TU Graz
TU Graz
Building a dense and accurate environment model out of range image data faces problems like sensor noise, extensive memory consumption or computation time. We present an approach which reconstructs 3D environments using a probabilistic occupancy grid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21bf7f7885e3b4e1eba19c11d3c87bca
https://doi.org/10.1109/iccvw.2011.6130377
https://doi.org/10.1109/iccvw.2011.6130377
Publikováno v:
BMVC
TU Graz
TU Graz
We propose a novel, hybrid SLAM system to construct a dense occupancy grid map based on sparse visual features and dense depth information. While previous approaches deemed the occupancy grid usable only in 2D mapping, and in combination with a proba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8138a60e53442804d0bcd1235983de14
https://doi.org/10.5244/c.25.115
https://doi.org/10.5244/c.25.115
Publikováno v:
ICARCV
Photonic mixer devices (PMDs) are able to create reliable depth maps of indoor environments. Yet, their application in mobile robotics, especially in simultaneous localization and mapping (SLAM) applications, is hampered by the limited field of view.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f99408d811bbbd416e37a77bf9e38442
https://doi.org/10.1109/icarcv.2010.5707286
https://doi.org/10.1109/icarcv.2010.5707286
Publikováno v:
BMVC
Simultaneous localization and mapping (SLAM) is a basic prerequisite in autonomous mobile robotics. Most existing visual SLAM approaches either assume a static environment, or simply ’forget’ old parts of the map to cope with map size constraints
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f7b4cab422a8db136461ac4ab22b67c
https://doi.org/10.5244/c.24.76
https://doi.org/10.5244/c.24.76
Publikováno v:
TU Graz
IROS
IROS
When performing large-scale perpetual localization and mapping one faces problems like memory consumption or repetitive and dynamic scene elements requiring robust data association. We propose a visual SLAM method which handles short- and long-term s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee611ad76a46d03c76666e134e6c9765
https://graz.pure.elsevier.com/en/publications/cd-slam--continuous-localization-and-mapping-in-a-dynamic-world(6362a938-8f7e-496b-b60c-4c87823395bb).html
https://graz.pure.elsevier.com/en/publications/cd-slam--continuous-localization-and-mapping-in-a-dynamic-world(6362a938-8f7e-496b-b60c-4c87823395bb).html
