Robust and Long-term Monocular Teach and Repeat Navigation using a Single-experience Map
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00357706" target="_blank" >RIV/68407700:21230/21:00357706 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/IROS51168.2021.9635886" target="_blank" >https://doi.org/10.1109/IROS51168.2021.9635886</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IROS51168.2021.9635886" target="_blank" >10.1109/IROS51168.2021.9635886</a>
Alternative languages
Result language
angličtina
Original language name
Robust and Long-term Monocular Teach and Repeat Navigation using a Single-experience Map
Original language description
This paper presents a robust monocular visual teach-and-repeat (VT&R) navigation system for long-term operation in outdoor environments. The approach leverages deep-learned descriptors to deal with the high illumination variance of the real world. In particular, a tailored self-supervised descriptor, DarkPoint, is proposed for autonomous navigation in outdoor environments. We seamlessly integrate the localisation with control, in which proportional-integral control is used to eliminate the visual error with the pitfall of the unknown depth. Consequently, our approach achieves day-to-night navigation using a single-experience map and is able to repeat complex and fast manoeuvres. To verify our approach, we performed a vast array of navigation experiments in various outdoor environments, where both navigation accuracy and robustness of the proposed system are investigated. The experimental results show that our approach is superior to the baseline method with regards to accuracy and robustness.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GC20-27034J" target="_blank" >GC20-27034J: Towards long-term autonomy through introduction of the temporal domain into spatial representations used in robotics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ISBN
978-1-6654-1714-3
ISSN
2153-0858
e-ISSN
2153-0866
Number of pages
8
Pages from-to
2635-2642
Publisher name
IEEE
Place of publication
Piscataway
Event location
Praha
Event date
Sep 27, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000755125502025