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Path Planning of Autonomous Underwater Vehicle Under Malicious Node Effect in Underwater Acoustic Sensor Networks

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Computer Vision and Robotics

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

Autonomous Underwater Vehicles (AUVs) are subject to various perturbations due to the harsh underwater environment. One such effect is the malicious node perturbation. To deal with effective sensor network coverage, an area-based path planning approach is proposed here, called the Voronoi Area Path Planning (VAP2) algorithm, which compensates for the node malice by segregating the coverage area into different regions based on Voronoi partitioning. It enhances the path planning capability and the coverage accuracy of the AUV nodes compared to the conventional techniques, as confirmed by the performance evaluation with respect to different parameters. The proposed VAP2 technique shall find immense application in naval search and rescue and other marine research operations.

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Acknowledgements

This work was supported by the Ministry of Electronics and Information Technology, Government of India, under Grant 13(29)/2020-CC&BT.

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Authors and Affiliations

  1. National Institute of Technology Patna, Ashok Rajpath, Patna, 800005, Bihar, India

    Arnav Hari,  Prateek & Rajeev Arya

Authors
  1. Arnav Hari
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  2. Prateek
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  3. Rajeev Arya
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Corresponding author

Correspondence to Prateek .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India

    Praveen Kumar Shukla

  2. Department of Information Technology, Indian Institute of Information Technology, Allahabad, Prayagraj, Uttar Pradesh, India

    Krishna Pratap Singh

  3. Department of Computer Science & Engineering, Malviya National Institute of Technology (MNIT), Jaipur, India

    Ashish Kumar Tripathi

  4. Department of Industrial Engineering and Computer Science Division, University of Stellenbosch, Matieland, South Africa

    Andries Engelbrecht

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Hari, A., Prateek, Arya, R. (2023). Path Planning of Autonomous Underwater Vehicle Under Malicious Node Effect in Underwater Acoustic Sensor Networks. In: Shukla, P.K., Singh, K.P., Tripathi, A.K., Engelbrecht, A. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-7892-0_19

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