UAV Vision-Based Nonlinear Formation Control Applied to Inspection of Electrical Power Lines

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00347474" target="_blank" >RIV/68407700:21230/20:00347474 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/ICUAS48674.2020.9213967" target="_blank" >https://doi.org/10.1109/ICUAS48674.2020.9213967</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUAS48674.2020.9213967" target="_blank" >10.1109/ICUAS48674.2020.9213967</a>

Jazyk výsledku

angličtina

Název v původním jazyce

UAV Vision-Based Nonlinear Formation Control Applied to Inspection of Electrical Power Lines

Popis výsledku v původním jazyce

Cooperation of humans workers and a team of UAV co-workers for inspection and maintenance of electrical power is the main motivation of research presented in this paper. Collaborative human-UAV works at height are beneficial from several reasons including providing images from the ideal point of view, monitoring of the safety of individual workers, and even aerial delivering of required tools. These tasks also involve cognitive capabilities in the monitoring of the workers and the detection of unsafe behaviors, transportation of tools or parts needed by the workers and collective manipulation with the workers. In general, interaction of humans and teams of UAVs becomes an important task as aerial robots are widely spread in various applications that require the presence of people in their workspace. To achieve such interaction, group control of multiple UAVs must take states of workers (e.g. position relative to aerial co-workers and prediction of worker's future behavior), maintaining an adaptable formation and maximizing the observation of the worker. Thus, we propose in this work, a distributed vision-based nonlinear formation control (DVNFC) approach that results in an adaptable formation where the controller minimizes the error in observation always maintaining the visualization of the human by the whole formation. We performed several numerical simulations using ROS/Gazebo with real-time visual feedback to validate our approach.

Název v anglickém jazyce

UAV Vision-Based Nonlinear Formation Control Applied to Inspection of Electrical Power Lines

Popis výsledku anglicky

Cooperation of humans workers and a team of UAV co-workers for inspection and maintenance of electrical power is the main motivation of research presented in this paper. Collaborative human-UAV works at height are beneficial from several reasons including providing images from the ideal point of view, monitoring of the safety of individual workers, and even aerial delivering of required tools. These tasks also involve cognitive capabilities in the monitoring of the workers and the detection of unsafe behaviors, transportation of tools or parts needed by the workers and collective manipulation with the workers. In general, interaction of humans and teams of UAVs becomes an important task as aerial robots are widely spread in various applications that require the presence of people in their workspace. To achieve such interaction, group control of multiple UAVs must take states of workers (e.g. position relative to aerial co-workers and prediction of worker's future behavior), maintaining an adaptable formation and maximizing the observation of the worker. Thus, we propose in this work, a distributed vision-based nonlinear formation control (DVNFC) approach that results in an adaptable formation where the controller minimizes the error in observation always maintaining the visualization of the human by the whole formation. We performed several numerical simulations using ROS/Gazebo with real-time visual feedback to validate our approach.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

International Conference on Unmanned Aircraft Systems (ICUAS)

ISBN

978-1-7281-4278-4

ISSN

2373-6720

e-ISSN

2575-7296

Počet stran výsledku

8

Strana od-do

1301-1308

Název nakladatele

IEEE

Místo vydání

Vancouver

Místo konání akce

Athens

Datum konání akce

1. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000612041300167