Mixed-initiative planning, replanning and execution: From concept to field testing using AUV fleets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315067" target="_blank" >RIV/68407700:21230/17:00315067 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IROS.2017.8206602" target="_blank" >http://dx.doi.org/10.1109/IROS.2017.8206602</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2017.8206602" target="_blank" >10.1109/IROS.2017.8206602</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mixed-initiative planning, replanning and execution: From concept to field testing using AUV fleets

Popis výsledku v původním jazyce

Mission planning and execution for autonomous vehicles is crucial for their effective and efficient operation during scientific exploration, or search and rescue missions, to mention a few. Automated Planning has shown to be a useful tool for ``high level'' mission planning, that is, allocating tasks to vehicles while following given constraints (e.g., energy, collision avoidance). In this paper, we focus on making mission planning flexible and robust. That is, a human mission coordinator can modify tasks during the mission execution, so the tasks have to be dynamically reallocated during the process. Moreover, we assume that communication might not be reliable when vehicles are ``outside'', i.e., performing the tasks, and thus we enforce vehicles to come back to their safe spots regularly. To address these requirements, we have developed two models, namely ``all tasks'' and ``one round'', and integrated them to the control software. We have evaluated our approach in a field experiment focused on a mine-hunting scenario.

Název v anglickém jazyce

Mixed-initiative planning, replanning and execution: From concept to field testing using AUV fleets

Popis výsledku anglicky

Mission planning and execution for autonomous vehicles is crucial for their effective and efficient operation during scientific exploration, or search and rescue missions, to mention a few. Automated Planning has shown to be a useful tool for ``high level'' mission planning, that is, allocating tasks to vehicles while following given constraints (e.g., energy, collision avoidance). In this paper, we focus on making mission planning flexible and robust. That is, a human mission coordinator can modify tasks during the mission execution, so the tasks have to be dynamically reallocated during the process. Moreover, we assume that communication might not be reliable when vehicles are ``outside'', i.e., performing the tasks, and thus we enforce vehicles to come back to their safe spots regularly. To address these requirements, we have developed two models, namely ``all tasks'' and ``one round'', and integrated them to the control software. We have evaluated our approach in a field experiment focused on a mine-hunting scenario.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IEEE International Conference on Robotics and Automation

ISBN

978-1-5386-2682-5

ISSN

2153-0858

e-ISSN

—

Počet stran výsledku

6

Strana od-do

6825-6830

Název nakladatele

IEEE Press

Místo vydání

New York

Místo konání akce

Vancouver

Datum konání akce

24. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—