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International Conference on Computational Logistics

ICCL 2016: Computational Logistics pp 65–79Cite as

Path Planning for Autonomous Inland Vessels Using A*BG

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9855))

Abstract

To meet the transportation demand and maintain sustainable development, many countries are aiming to promote the competitive position of inland waterway shipping in the transport system. Autonomous transport is seen as a possibility for maritime transport to meet today’s and tomorrow’s challenges. In realizing autonomous navigation, path planning plays an important role. Being the most widely used path planning algorithm for robotics and land-based vehicles, in this paper we analyze A* and its extensions for waterborne applications. We hereby exploit the fact that for vessels optimal paths typically have heading changes only at the corners of obstacles to propose a more efficient modified A* algorithm, A*BG, for autonomous inland vessels. Two locations where ship accidents frequently occur are considered in simulation experiments, in which the performance of A*, A*PS, Theta* and A*BG are compared.

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Acknowledgment

This research is supported by the China Scholarship Council under Grant 201426950041.

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Authors and Affiliations

  1. Department of Maritime and Transport Technology, Delft University of Technology, Delft, The Netherlands

    Linying Chen, Rudy R. Negenborn & Gabriel Lodewijks

Authors
  1. Linying Chen
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  2. Rudy R. Negenborn
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  3. Gabriel Lodewijks
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Corresponding author

Correspondence to Linying Chen .

Editor information

Editors and Affiliations

  1. Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal

    Ana Paias

  2. University of Vienna , Vienna, Austria

    Mario Ruthmair

  3. University of Hamburg , Hamburg, Hamburg, Germany

    Stefan Voß

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© 2016 Springer International Publishing Switzerland

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Chen, L., Negenborn, R.R., Lodewijks, G. (2016). Path Planning for Autonomous Inland Vessels Using A*BG. In: Paias, A., Ruthmair, M., Voß, S. (eds) Computational Logistics. ICCL 2016. Lecture Notes in Computer Science(), vol 9855. Springer, Cham. https://doi.org/10.1007/978-3-319-44896-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-44896-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44895-4

  • Online ISBN: 978-3-319-44896-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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