Machine Learning Algorithms for Multiple Autonomous Unmanned Vehicle Operations – Research Proposal

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Authors
  1. Wang, X.
  2. Shao, H.
Corporate Authors
Defence R&D Canada - Centre for Operational Research and Analysis, Ottawa ON (CAN);Nathalie Japkowicz Consulting Services, Hampstead QC (CAN)
Abstract
Autonomous Underwater Vehicles (AUVs) are expected to be used by military forces to acquire high-resolution sonar imagery for the detection of mines and other objects of interest on the seabed. This document reviews progress in the development of automated detection and classification techniques for side-looking sonar mounted on AUVs. While considerable progress has been made in both unsupervised and supervised (trained) algorithms for data processing and classification, this report focuses on the areas that are still lacking and require further research. From our analysis, a clear direction for future research is mapped. In particular, we explain what the classification algorithms that we plan to develop will aim to achieve.

Il y a un résumé en français ici.

Keywords
machine learning;MCM;AUV;unmanned vehicles
Report Number
DRDC-CORA-CR-2012-154 — Contract Report
Date of publication
01 Jun 2012
Number of Pages
27
DSTKIM No
CA043050
CANDIS No
804335
Format(s):
Electronic Document(PDF)

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