Zhao, C., Sun, L. orcid.org/0000-0002-0393-8665, Krajnik, T. et al. (2 more authors) (2021) Monocular teach-and-repeat navigation using a deep steering network with scale estimation. In: Proceedings of 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 27 Sep - 01 Oct 2021, Virtual conference (Prague, Czech Republic). IEEE , pp. 2613-2619. ISBN 9781665417150
Abstract
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. The proposed network is integrated into an onboard system deployed on a real robot to achieve real-time navigation in a real environment. A demonstration video can be found online: https://youtu.be/ctlwDaMKnHw
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Navigation; Estimation; Computer architecture; Streaming media; Visual servoing; Real-time systems; Task analysis |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/R026092/1 The Royal Society RGS\R2\202432 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Apr 2021 09:49 |
Last Modified: | 22 Feb 2022 20:25 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IROS51168.2021.9635912 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172958 |