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Real-Time Terrain Classification for Rescue Robot Based on Extreme Learning Machine

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Cognitive Systems and Signal Processing (ICCSIP 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 710))

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Abstract

Full autonomous robots in urban search and rescue (USAR) have to deal with complex terrains. The real-time recognition of terrains in front could effectively improve the ability of pass for rescue robots. This paper presents a real-time terrain classification system by using a 3D LIDAR on a custom designed rescue robot. Firstly, the LIDAR state estimation and point cloud registration are running in parallel to extract the test lane region. Secondly, normal aligned radial feature (NARF) is extracted and downscaled by a distance based weighting method. Finally, an extreme learning machine (ELM) classifier is designed to recognize the types of terrains. Experimental results demonstrate the effectiveness of the proposed system.

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Notes

  1. 1.

    http://wiki.robocup.org/wiki/Robot_League.

  2. 2.

    http://nubot.trustie.com/videos.

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Acknowledgements

Our work is supported by National Science Foundation of China (NO. 61503401 and NO. 61403409), China Postdoctoral Science Foundation (NO. 2014M562648), and graduate school of National University of Defense Technology. All members of the NuBot research group are gratefully acknowledged.

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Authors and Affiliations

  1. College of Mechatronics and Automation, National University of Defense Technology, Changsha, 410073, Hunan, China

    Yuhua Zhong, Junhao Xiao, Huimin Lu & Hui Zhang

Authors
  1. Yuhua Zhong
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  2. Junhao Xiao
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  3. Huimin Lu
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  4. Hui Zhang
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Corresponding author

Correspondence to Junhao Xiao .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Fuchun Sun

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Huaping Liu

  3. College of Mechatronics and Automation, National University of Defense Technology, Changsha, China

    Dewen Hu

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Zhong, Y., Xiao, J., Lu, H., Zhang, H. (2017). Real-Time Terrain Classification for Rescue Robot Based on Extreme Learning Machine. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2016. Communications in Computer and Information Science, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-5230-9_38

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  • DOI: https://doi.org/10.1007/978-981-10-5230-9_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5229-3

  • Online ISBN: 978-981-10-5230-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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