On AUV actions to correctly label world information

Francesco Maurelli, Zeyn Saigol, David Lane, Michael Cashmore, Bram Ridder, Daniele Magazzeni

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

An Autonomous Underwater Vehicle (AUV) needs to demonstrate a number of capabilities, in order to carry on autonomous missions with success. One of the key areas is correctly understanding the surrounding environment. However, most of the state-of-the-art approaches in labelling world information are based on the analysis of a single frame, whilst - especially in scenarios where the vehicle interact with complex structures - there is the need of sensor data from multiple views, in order to correctly classify world information. This paper presents an active approach to solve this problem, with a tree-based (path)-planner which makes the vehicle executing a specific set of actions (following a specific trajectory), in order to discriminate among several possibilities. Results in simulation, with varying parameters, have shown that the algorithm is always bringing the robot to locations where it is expected that measurements would be different, according to the different environment.
Original languageEnglish
Title of host publicationProceedings of OCEANS 2014
PublisherIEEE
Number of pages6
ISBN (Print)9781479949182
DOIs
Publication statusPublished - 8 Jan 2015
EventOceans 2014 MTS/IEEE - St. John's, Canada
Duration: 14 Sep 201419 Sep 2014

Conference

ConferenceOceans 2014 MTS/IEEE
CountryCanada
CitySt. John's
Period14/09/1419/09/14

Keywords

  • autonomous underwater vehicle (AUV)

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