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SeDAR - Semantic Detection and Ranging: Humans can localise without LiDAR, can robots?
[article]
2018
arXiv
pre-print
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And yet, this is how most vision-based approaches localise. Humans do the exact opposite. Instead of depth, we use high level semantic cues. ...
While our approach is able to use range measurements if available, we demonstrate that they are unnecessary as we can achieve results comparable to state-of-the-art without them. ...
Semantic Detection and Ranging (SeDAR) is an innovative human-inspired framework that combines new semantic sensing capabilities with a novel semantic Monte-Carlo Localisation (MCL) approach. ...
arXiv:1709.01500v2
fatcat:gxiyci7qyvg6hixcmcj7vwi7t4
SeDAR - Semantic Detection and Ranging: Humans can Localise without LiDAR, can Robots?
2018
2018 IEEE International Conference on Robotics and Automation (ICRA)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
And yet, this is how most vision-based approaches localise. Humans do the exact opposite. Instead of depth, we use high level semantic cues. ...
While our approach is able to use range measurements if available, we demonstrate that they are unnecessary as we can achieve results comparable to state-of-the-art without them. ...
Semantic Detection and Ranging (SeDAR) is an innovative human-inspired framework that combines new semantic sensing capabilities with a novel semantic Monte-Carlo Localisation (MCL) approach. ...
doi:10.1109/icra.2018.8461074
dblp:conf/icra/MaldonadoHPB18
fatcat:dqzyqgou4jdwtdgfmy5pyukkji
SeDAR: Reading Floorplans Like a Human—Using Deep Learning to Enable Human-Inspired Localisation
2019
International Journal of Computer Vision
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The use of human-level semantic information to aid robotic tasks has recently become an important area for both Computer Vision and Robotics. ...
While our approach is able to use range measurements if available, we demonstrate that they are unnecessary as we can achieve results comparable to state-of-the-art without them. ...
Semantic Detection and Ranging (SeDAR) is an innovative human-inspired framework that combines new semantic sensing capabilities with a novel semantic Monte-Carlo Localisation (MCL) approach. ...
doi:10.1007/s11263-019-01239-4
fatcat:hd2lcseet5ecffjry3hbfjviia