Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/91436
Title: Intelligent shipwreck search using autonomous underwater vehicles
Authors: Rutledge, Jeffrey
Wentao, Yuan
Freed, Sam
Lewis, Amy
Wood, Zoe J.
Gambin, Timmy
Clark, Christopher M.
Keywords: Autonomous underwater vehicles
Underwater archaeology -- Data processing -- Case studies
Underwater exploration -- Malta
Shipwrecks -- Malta
Underwater archaeology -- Malta -- Data processing
Issue Date: 2018
Publisher: IEEE
Citation: Rutledge, J., Yuan, W., Wu, J., Freed, S., Lewis, S., Wood, Z.,...T., Clark, C. (2018). Intelligent shipwreck search using autonomous underwater vehicles. IEEE International Conference on Robotics and Automation (ICRA), Australia, 6175 - 6182.
Abstract: his paper presents an autonomous robot system that is designed to autonomously search for and geo-localize potential underwater archaeological sites. The system, based on Autonomous Underwater Vehicles, invokes a multi-step pipeline. First, the AUV constructs a high altitude scan over a large area to collect low-resolution side scan sonar data. Second, image processing software is employed to automatically detect and identify potential sites of interest. Third, a ranking algorithm assigns importance scores to each site. Fourth, an AUV path planner is used to plan a time-limited path that visits sites with a high importance at a low altitude to acquire high-resolution sonar data. Last, the AUV is deployed to follow this path. This system was implemented and evaluated during an archaeological survey located along the coast of Malta. These experiments demonstrated that the system is able to identify valuable archaeological sites accurately and efficiently in a large previously unsurveyed area. Also, the planned missions led to the discovery of a historical plane wreck whose location was previously unknown.
URI: https://www.um.edu.mt/library/oar/handle/123456789/91436
Appears in Collections:Scholarly Works - FacArtCA

Files in This Item:
File Description SizeFormat 
Intelligent_shipwreck_search_using_autonomous_underwater_vehicles(2018).pdf
  Restricted Access
4.58 MBAdobe PDFView/Open Request a copy


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.