Assessment of Collision Avoidance Strategies for an Underwater Transportation System

Faheem Ur Rehman; Enrico Anderlini; Giles Thomas

doi:10.18196/jrc.25112

Authors

Faheem Ur Rehman University College London, UK https://orcid.org/0000-0003-0914-2139
Enrico Anderlini University College London, UK https://orcid.org/0000-0002-8860-8330
Giles Thomas University College London, UK

DOI:

https://doi.org/10.18196/jrc.25112

Keywords:

Autonomous Underwater Vehicle (AUV), underwater transportation, multi vehicles, sensor-based methods, path planning method, PID controller

Abstract

Transportation using multiple autonomous vehicles with detection avoidance capability is useful for military applications. It is important for such systems to avoid collisions with underwater obstacles in an effective way, while keeping track of the target location. In this paper, sensor-based and path-planning methods of external collision avoidance were investigated for an underwater transportation system. In particular, sensor-based wall-following and hard-switching collision avoidance strategies and an offline RRT* path-planning method was implemented on the simulation model of the transportation system of four Hovering Autonomous Underwater Vehicles (HAUVs). Time-domain motion simulations were performed with each method and their ability to avoid obstacles was compared. The hard-switching method resulted in high yaw moments which caused the vehicle to travel towards the goal by a longer distance. Conversely, in the wall-following method, the yaw moment was kept to zero. Moreover, the wall-following method was found to be better than the hard-switching method in terms of time and power efficiency. The comparison between the offline RRT* path-planning and wall-following methods showed that the fuel efficiency of the former is higher whilst its time efficiency is poorer. The major drawback of RRT* is that it can only avoid the previously known obstacles. In future, offline RRT* and wall following can be blended for a better solution. The outcome of this paper provides guidance for the selection of the most appropriate method for collision avoidance for an underwater transportation system.

Author Biographies

Faheem Ur Rehman, University College London, UK

Faheem Ur Rehman is currently undertaking PhD studies at UCL Mechanical Engineering department. His field of research is autonomous underwater transportation using multiple autonomous vehicles. He is a Member of the Royal Institute of Naval Architects (RINA) and a student member of the Society of Naval Architects and Marine Engineers (SNAME).

Enrico Anderlini, University College London, UK

Dr Enrico Anderlini is a senior research associate at UCL Mechanical Engineering. He teaches ocean engineering at undergraduate and postgraduate level and provides support to the ship and submarine design exercises. During his doctorate, Enrico developed control strategies for wave energy converters using reinforcement learning. He is an Associate Member of the Royal Institute of Naval Architects (RINA).

Giles Thomas, University College London, UK

Professor Giles Thomas is BMT Chair of Maritime Engineering in University College London’s Department of Mechanical Engineering. A naval architect, his research focusses on the performance of ships, boats and offshore structures. Specific interests include fluid-structure interaction, hydrodynamics, full-scale measurements, model testing and design. He is a Fellow of the Royal Institution of Naval Architects (RINA) and a Chartered Engineer (CEng – Engineering Council of Great Britain).

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