Autonomous landing on a moving vehicle with an unmanned aerial vehicle

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00326172" target="_blank" >RIV/68407700:21230/19:00326172 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1002/rob.21858" target="_blank" >https://doi.org/10.1002/rob.21858</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/rob.21858" target="_blank" >10.1002/rob.21858</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Autonomous landing on a moving vehicle with an unmanned aerial vehicle

Popis výsledku v původním jazyce

This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year-long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.

Název v anglickém jazyce

Autonomous landing on a moving vehicle with an unmanned aerial vehicle

Popis výsledku anglicky

This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year-long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/GJ17-16900Y" target="_blank" >GJ17-16900Y: Stabilizace a řízení týmů vzájemně lokalizovaných autonomních helikoptér letících oblastmi s velkým výskytem překážek</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Journal of Field Robotics

ISSN

1556-4959

e-ISSN

1556-4967

Svazek periodika

36

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

874-891

Kód UT WoS článku

000475466200002

EID výsledku v databázi Scopus

2-s2.0-85059557991