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International Conference on Computer Vision Systems

ICVS 2017: Computer Vision Systems pp 471–484Cite as

A Cloud-Based Visual SLAM Framework for Low-Cost Agents

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 10528)

Abstract

Constrained by on-board resource, most of the low-cost robots could not autonomously navigate in unknown environments. In the latest years, cloud computing and storage has been developing rapidly, making it possible to offload parts of visual SLAM processing to a server. However, most of the cloud-based vSLAM frameworks are not suitable or fully tested for the applications of poor-equipped agents. In this paper, we describe an online localization service on a novel cloud-based framework, where the expensive map storage and global feature matching are provided as a service to agents. It enables a scenario that only sensor data collection is executed on agents, while the cloud aids the agents to localize and navigate. At the end, we evaluate the localization service quantitatively and qualitatively. The results indicate that the proposed cloud framework can fit the requirement of real-time applications.

Keywords

  • Cloud robotics
  • Mobile robot
  • Visual SLAM

This work was sponsored by the Research Grant Council of Hong Kong SAR Government, China, under project Nos. 16212815, 21202816 and National Natural Science Foundation of China Nos. 6140021318 and 61640305; Shenzhen Science, Technology and Innovation Comission (SZSTI) JCYJ20160428154842603 and JCYJ20160401100022706; partially supported by the HKUST Project IGN16EG12. All rewarded to Prof. Ming Liu.

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  • DOI: 10.1007/978-3-319-68345-4_42
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Notes

  1. 1.

    OpenResty: a registered trademark owned by OpenResty Inc. https://openresty.org.

  2. 2.

    OrangePi Plus2: http://www.orangepi.org/orangepiplus2.

  3. 3.

    JSON: a lightweight data-interchange that is easy for humans to read and write. http://www.json.org.

  4. 4.

    RapidJSON: a fast JSON parser/generator for C++. http://rapidjson.org.

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Authors and Affiliations

  1. Robotics and Multi-perception Lab (RAM-LAB), Robotics Institute, The Hong Kong University of Science and Technology, Hong Kong, China

    Jianhao Jiao, Peng Yun & Ming Liu

Authors
  1. Jianhao Jiao
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  2. Peng Yun
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  3. Ming Liu
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Corresponding author

Correspondence to Jianhao Jiao .

Editor information

Editors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong, China

    Ming Liu

  2. Harbin Institute of Technology, Shenzhen, China

    Dr. Haoyao Chen

  3. Technische Universtiät Wien, Vienna, Austria

    Prof. Dr. Markus Vincze

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Jiao, J., Yun, P., Liu, M. (2017). A Cloud-Based Visual SLAM Framework for Low-Cost Agents. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_42

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  • DOI: https://doi.org/10.1007/978-3-319-68345-4_42

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