Unsupervised learning-based flexible framework for surveillance planning with aerial vehicles

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00323909" target="_blank" >RIV/68407700:21230/19:00323909 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1002/rob.21823" target="_blank" >https://doi.org/10.1002/rob.21823</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/rob.21823" target="_blank" >10.1002/rob.21823</a>

Result language

angličtina

Original language name

Unsupervised learning-based flexible framework for surveillance planning with aerial vehicles

Original language description

The herein studied problem is motivated by practical needs of our participation in the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 in which a team of unmanned aerial vehicles (UAVs) is requested to collect objects in the given area as quickly as possible and score according to the rewards associated with the objects. The mission time is limited, and the most time-consuming operation is the collection of the objects themselves. Therefore, we address the problem to quickly identify the most valuable objects as surveillance planning with curvature-constrained trajectories. The problem is formulated as a multivehicle variant of the Dubins traveling salesman problem with neighborhoods (DTSPN). Based on the evaluation of existing approaches to the DTSPN, we propose to use unsupervised learning to find satisfiable solutions with low computational requirements. Moreover, the flexibility of unsupervised learning allows considering trajectory parametrization that better fits the motion constraints of the utilized hexacopters that are not limited by the minimal turning radius as the Dubins vehicle. We propose to use Bézier curves to exploit the maximal vehicle velocity and acceleration limits. Besides, we further generalize the proposed approach to 3D surveillance planning. We report on evaluation results of the developed algorithms and experimental verification of the planned trajectories using the real UAVs utilized in our participation in MBZIRC 2017.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

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

Name of the periodical

Journal of Field Robotics

ISSN

1556-4959

e-ISSN

1556-4967

Volume of the periodical

36

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

32

Pages from-to

270-301

UT code for WoS article

000455132600015

EID of the result in the Scopus database

2-s2.0-85054572303