Opportunistic planning in autonomous underwater missions

Cashmore, Michael and Fox, Maria and Long, Derek and Magazzeni, Daniele and Ridder, Bram (2018) Opportunistic planning in autonomous underwater missions. IEEE Transactions on Automation Science and Engineering, 15 (2). pp. 519-530. ISSN 1545-5955 (https://doi.org/10.1109/TASE.2016.2636662)

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Abstract

This paper explores the execution of planned autonomous underwater vehicle (AUV) missions where opportunities to achieve additional utility can arise during execution. The missions are represented as temporal planning problems, with hard goals and time constraints. Opportunities are soft goals with high utility. The probability distributions for the occurrences of these opportunities are not known, but it is known that they are unlikely, so it is not worth trying to anticipate their occurrence prior to plan execution. However, as they are high utility, it is worth trying to address them dynamically when they are encountered, as long as this can be done without sacrificing the achievement of the hard goals of the problem. We formally characterize the opportunistic planning problem, introduce a novel approach to opportunistic planning, and compare it with an on-board replanning approach in the domain of AUVs performing pillar expection and chain-following tasks.

ORCID iDs

Cashmore, Michael ORCID logoORCID: https://orcid.org/0000-0002-8334-4348, Fox, Maria, Long, Derek, Magazzeni, Daniele and Ridder, Bram;
  • Item type:Article
    ID code:69963
    Dates:
    Date
    Event
    1 April 2018
    Published
    20 January 2017
    Published Online
    29 October 2016
    Accepted
    Notes:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:26 Sep 2019 11:41
    Last modified:17 Nov 2024 01:16
    URI:https://strathprints.strath.ac.uk/id/eprint/69963
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