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Obstacle Avoidance Approaches for Autonomous Navigation of Unmanned Surface Vehicles

Published online by Cambridge University Press:  10 October 2017

Riccardo Polvara Open the ORCID record for Riccardo Polvara [Opens in a new window] ,
Sanjay Sharma ,
Jian Wan ,
Andrew Manning  and
Robert Sutton
Riccardo Polvara*
Affiliation:
(Autonomous Marine Systems Research Group, Faculty of Science and Engineering, University of Plymouth, Plymouth, Devon, PL4 8AA, UK)
Sanjay Sharma
Affiliation:
(Autonomous Marine Systems Research Group, Faculty of Science and Engineering, University of Plymouth, Plymouth, Devon, PL4 8AA, UK)
Jian Wan
Affiliation:
(Autonomous Marine Systems Research Group, Faculty of Science and Engineering, University of Plymouth, Plymouth, Devon, PL4 8AA, UK)
Andrew Manning
Affiliation:
(Autonomous Marine Systems Research Group, Faculty of Science and Engineering, University of Plymouth, Plymouth, Devon, PL4 8AA, UK) (HR Wallingford, Howbery Park, Wallingford, Oxfordshire, OX10 8BA, UK) (Geography & Geology, School of Environmental Sciences, Faculty of Science & Engineering, University of Hull, Hull, HU6 7RX, UK)
Robert Sutton
Affiliation:
(Autonomous Marine Systems Research Group, Faculty of Science and Engineering, University of Plymouth, Plymouth, Devon, PL4 8AA, UK)
*
(E-mail: riccardo.polvara@plymouth.ac.uk)
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Abstract

The adoption of a robust collision avoidance module is required to realise fully autonomous Unmanned Surface Vehicles (USVs). In this work, collision detection and path planning methods for USVs are presented. Attention is focused on the difference between local and global path planners, describing the most common techniques derived from classical graph search theory. In addition, a dedicated section is reserved for intelligent methods, such as artificial neural networks and evolutionary algorithms. Born as optimisation methods, they can learn a close-to-optimal solution without requiring large computation effort under certain constraints. Finally, the deficiencies of the existing methods are highlighted and discussed. It has been concluded that almost all the existing method do not address sea or weather conditions, or do not involve the dynamics of the vessel while defining the path. Therefore, this research area is still far from being considered fully explored.

Keywords

Unmanned Surface VehicleCollision AvoidancePath Planning
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 1 , January 2018 , pp. 241 - 256
Copyright
Copyright © The Royal Institute of Navigation 2017 

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References

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