Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Sascha Wirges"'
Publikováno v:
Sensors, Vol 21, Iss 10, p 3380 (2021)
Accurately estimating the current state of local traffic scenes is one of the key problems in the development of software components for automated vehicles. In addition to details on free space and drivability, static and dynamic traffic participants
Externí odkaz:
https://doaj.org/article/f1f29e02e35e4eaeaf30473e4040395a
Publikováno v:
2022 25th International Conference on Information Fusion (FUSION).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a779be74eb5278dfb9e8122a870b2db
https://doi.org/10.23919/fusion49751.2022.9841241
https://doi.org/10.23919/fusion49751.2022.9841241
Publikováno v:
tm - Technisches Messen. 88:352-360
In this work, we improve the semantic segmentation of multi-layer top-view grid maps in the context of LiDAR-based perception for autonomous vehicles. To achieve this goal, we fuse sequential information from multiple consecutive LiDAR measurements w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a231b3639c6dc02c34a430c1c3c60b0
https://doi.org/10.1515/teme-2021-0026
https://doi.org/10.1515/teme-2021-0026
We propose a fast and robust method to estimate the ground surface from LIDAR measurements on an automated vehicle. The ground surface is modeled as a UBS which is robust towards varying measurement densities and with a single parameter controlling t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2de6e73d7c3badf53f4ca47bfc137ad7
Publikováno v:
tm - Technisches Messen. 86:102-106
A detailed reconstruction of the environment is a crucial component of mobile robotic systems and enables higher level scene understanding. To achieve information redundancy heterogenous sensors need to be used with each sensor having specific streng
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0da27b09118218240e5dec1fac44d23f
https://doi.org/10.1515/teme-2019-0052
https://doi.org/10.1515/teme-2019-0052
Publikováno v:
IFAC-PapersOnLine. 52:87-92
Estimating motion and shape of surrounding objects reliably and accurately is a fundamental challenge in the study of interactions between cooperative traffic participants. This paper proposes a new approach that utilizes free space information obtai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e6ede9eafe825b3aca3e39f6d6ff9a0
https://doi.org/10.1016/j.ifacol.2019.08.053
https://doi.org/10.1016/j.ifacol.2019.08.053
Autor:
Frank Bieder, Johannes Janosovits, Zheyuan Wang, Sascha Wirges, Sven Richter, Christoph Stiller
Publikováno v:
IV
In this paper, we consider the transformation of laser range measurements into a top-view grid map representation to approach the task of LiDAR-only semantic segmentation. Since the recent publication of the SemanticKITTI data set, researchers are no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::359629efe6e3b5b49013e840b0414828
https://doi.org/10.1109/iv47402.2020.9304848
https://doi.org/10.1109/iv47402.2020.9304848
Publikováno v:
MFI
Accurately estimating the current state of local traffic scenes is a crucial component of automated vehicles. The desired representation may include static and dynamic traffic participants, details on free space and drivability, but also information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f21e7913ded9d8d1ae1265766372f292
https://doi.org/10.1109/mfi49285.2020.9235217
https://doi.org/10.1109/mfi49285.2020.9235217
Publikováno v:
MFI
3D pedestrian detection is a challenging task in automated driving because pedestrians are relatively small, frequently occluded and easily confused with narrow vertical objects. LiDAR and camera are two commonly used sensor modalities for this task,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c12d2ef26c44f9879ff133c66e896ec
https://doi.org/10.1109/mfi49285.2020.9235240
https://doi.org/10.1109/mfi49285.2020.9235240
Publikováno v:
IV
We present our approach to unsupervised domain adaptation for single-stage object detectors on top-view grid maps in automated driving scenarios. Our goal is to train a robust object detector on grid maps generated from custom sensor data and setups.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c89bc8fa5bbd14773ab4c89f2dd8c3f5
http://arxiv.org/abs/2002.00667
http://arxiv.org/abs/2002.00667