Towards an online heuristic method for energy-constrained underwater sensing mission planning

Nikolaos Tsiogkas, Valerio De Carolis, David Michael Lane

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

2 Citations (Scopus)

Abstract

Autonomous Underwater Vehicles (AUVs) have been widely used in scientific or industrial operations over the past years. AUV missions require the vehicle to perform a set of actions autonomously and return to the operators. These missions are currently mostly planned offline by the human operators. Existing solutions in commercial planning software usually only provide an estimate of the mission execution time. The uncertain and dynamic underwater environment can have an effect on the mission performance. More time and energy may be required, disallowing successful mission execution. This work proposes the usage of the correlated orienteering problem (COP) that maximises the utility of a sensing mission while respecting energy and time constraints. We propose a heuristic-based on genetic algorithms (GA) for the solution of the COP. This heuristic is compared against optimal mixed-integer quadratic programming (MIQP) solutions. Results show that the quality of the heuristic solution is in the worst tested case 5.5% less than the 1% optimal solutions. The heuristic proves to be at least 3 times more time efficient than the optimal MIQP solutions in the worst case. The heuristic is finally tested on an embedded platform showing its ability to be used on real robotic platforms.

Original languageEnglish
Title of host publication2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Pages6801-6808
Number of pages8
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 14 Dec 2017
Event30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017 - Vancouver, Canada
Duration: 24 Sep 201728 Sep 2017

Publication series

NameIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
ISSN (Electronic)2153-0866

Conference

Conference30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017
Abbreviated titleIROS 2017
CountryCanada
CityVancouver
Period24/09/1728/09/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Tsiogkas, N., De Carolis, V., & Lane, D. M. (2017). Towards an online heuristic method for energy-constrained underwater sensing mission planning. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6801-6808). (IEEE/RSJ International Conference on Intelligent Robots and Systems). IEEE. https://doi.org/10.1109/IROS.2017.8206599