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Advances in Signal Processing and Intelligent Recognition Systems pp 521–531Cite as

Multi-view Robotic Time Series Data Clustering and Analysis Using Data Mining Techniques

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 425))

Abstract

In present world robots are used in various spheres of life. In all these areas, knowledge of the environment is required to perform appropriate actions. The information about the environment is collected with the help of onboard sensors and image capturing device mounted on the mobile robot. As the information collected is of huge volume, data mining offers the possibility of discovering the hidden knowledge from this large amount of data. Clustering is an important aspect of data mining which will be explored in detail for grouping the scenario from multiple views.

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Author information

Authors and Affiliations

  1. Amrita Vishwa Vidyapeetham, Bangalore, India

    M. Reshma, Priyanka C. Nair, Radhakrishnan Gopalapillai, Deepa Gupta & TSB Sudarshan

Authors
  1. M. Reshma
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  2. Priyanka C. Nair
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  3. Radhakrishnan Gopalapillai
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  4. Deepa Gupta
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  5. TSB Sudarshan
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Corresponding author

Correspondence to M. Reshma .

Editor information

Editors and Affiliations

  1. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. Department of Electrical, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  4. Providence University, Taichung, Taiwan

    Kuan-Ching Li

  5. Computer Engineering Department, Vladimir State University, Vladimir Region, Russia

    Sergey Mosin

  6. School of Electrical, Nanyang Technological University, Singapore, Singapore

    Maode Ma

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Reshma, M., Nair, P.C., Gopalapillai, R., Gupta, D., Sudarshan, T. (2016). Multi-view Robotic Time Series Data Clustering and Analysis Using Data Mining Techniques. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_44

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  • DOI: https://doi.org/10.1007/978-3-319-28658-7_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28656-3

  • Online ISBN: 978-3-319-28658-7

  • eBook Packages: EngineeringEngineering (R0)

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