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An Energy Efficient Coverage Path Planning Approach for Mobile Robots

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Intelligent Computing (SAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 857))

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Abstract

An energy efficient online approach for performing coverage task in an unknown environment proposed in this paper. Although, energy consumption is an important optimality criteria, the current state of the art backtracking path planning approaches do not consider energy consumption required by robot to follow the path. This paper presents an energy efficient backtracking path planning approach for performing coverage task. The simulation results and comparative analysis show that the proposed approach gives better performance in time and memory requirements along with shorter path lengths.

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Acknowledgments

This study is supported by the research grant of Higher Education Commission (HEC) of Pakistan (No. 20-2359/NRPU/R&D/HEC/12-6779).

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Authors and Affiliations

  1. Department of Computer Science and Information Technology, The Superior College, Lahore, Pakistan

    Amna Khan

  2. Department of Software Engineering, The University of Lahore, Lahore, Pakistan

    Iram Noreen

  3. Department of Computer Science, COMSATS Institute of Information Technology, Lahore, Pakistan

    Amna Khan, Iram Noreen & Zulfiqar Habib

Authors
  1. Amna Khan
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  2. Iram Noreen
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  3. Zulfiqar Habib
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Corresponding author

Correspondence to Amna Khan .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Department of Information Science, Saga University, Honjo, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Khan, A., Noreen, I., Habib, Z. (2019). An Energy Efficient Coverage Path Planning Approach for Mobile Robots. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 857. Springer, Cham. https://doi.org/10.1007/978-3-030-01177-2_28

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