Strategic-tactical planning for autonomous underwater vehicles over long horizons

Dorian Buksz, Michael Cashmore, Benjamin Krarup, Daniele Magazzeni, Bram Ridder

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

13 Citations (Scopus)

Abstract

In challenging environments where human intervention is expensive, robust and persistent autonomy is a key requirement. AI Planners can efficiently construct plans to achieve this long-term autonomous behaviour. However, in plans which are expected to last over days, or even weeks, the size of the state-space becomes too large for current planners to solve as a single problem. These problems are well-suited to decomposition and abstraction planning techniques. We present a novel approach in the context of persistent autonomy in autonomous underwater vehicles, in which tasks are complex and diverse and plans cannot be precomputed. Our approach performs a decomposition into a two-level hierarchical structure, which dynamically constructs planning problems at the upper level of the hierarchy using solution plans from the lower level. Solution plans are then executed and monitored simultaneously at both levels. We evaluate the approach, showing that compared to strictly top-down hierarchical decompositions, our approach leads to more robust solution plans of higher quality.
Original languageEnglish
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages3565-3572
Number of pages8
ISBN (Electronic)9781538680940
ISBN (Print)9781538680940
DOIs
Publication statusPublished - 7 Jan 2019
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Madrid, Spain
Duration: 1 Oct 20185 Oct 2018

Conference

Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Abbreviated titleIROS2018
Country/TerritorySpain
CityMadrid
Period1/10/185/10/18

Keywords

  • task analysis
  • planning
  • manifolds
  • batteries
  • inspection
  • robots
  • valves
  • autonomous underwater vehicles
  • control engineering computing
  • mobile robots
  • planning (artificial intelligence)
  • robot dynamics
  • vehicle dynamics

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