Monocular Teach-and-Repeat Navigation using a Deep Steering Network with Scale Estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00357705" target="_blank" >RIV/68407700:21230/21:00357705 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/IROS51168.2021.9635912" target="_blank" >https://doi.org/10.1109/IROS51168.2021.9635912</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IROS51168.2021.9635912" target="_blank" >10.1109/IROS51168.2021.9635912</a>
Alternative languages
Result language
angličtina
Original language name
Monocular Teach-and-Repeat Navigation using a Deep Steering Network with Scale Estimation
Original language description
This paper proposes a novel monocular teach-and-repeat navigation system with the capability of scale awareness, i.e. the absolute distance between observation and goal images. It decomposes the navigation task into a sequence of visual servoing sub-tasks to approach consecutive goal/node images in a topological map. To be specific, a novel hybrid model, named deep steering network is proposed to infer the navigation primitives according to the learned local feature and scale for each visual servoing sub-task. A novel architecture, Scale-Transformer, is developed to estimate the absolute scale between the observation and goal image pair from a set of matched deep representations to assist repeating navigation. The experiments demonstrate that our scale-aware teach-and-repeat method achieves satisfying navigation accuracy, and converges faster than the monocular methods without scale correction given an inaccurate initial pose.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
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
7
Pages from-to
2613-2619
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
000755125502022