Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00347473" target="_blank" >RIV/68407700:21230/20:00347473 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/ICUAS48674.2020.9213924" target="_blank" >https://doi.org/10.1109/ICUAS48674.2020.9213924</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUAS48674.2020.9213924" target="_blank" >10.1109/ICUAS48674.2020.9213924</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles

Popis výsledku v původním jazyce

Highly dynamic systems such as Micro Multirotor Aerial Vehicles (Micro-MAVs) require control approaches that enable safe operation where extreme limitations in embedded systems, such as energy, processing capability and memory, are present. Nonlinear model predictive control (NMPC) approaches can respect operational constraints in a safe manner. However, they are typically challenging to implement using embedded computers on-board of Micro-MAVs. Implementations of classic NMPC approaches rely on high-performance computers. In this work, we propose a fast nonlinear model predictive control approach that ensures the stabilization and control of Micro Multirotor Aerial Vehicles (Micro-MAVs). This aerial robotic system uses a low processing power board that relies solely on on-board sensors to localize itself, which makes it suitable for experiments in GPS-denied environments. The proposed approach has been verified in numerical simulations using processing capabilities that are available on Micro-MAVs.

Název v anglickém jazyce

Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles

Popis výsledku anglicky

Highly dynamic systems such as Micro Multirotor Aerial Vehicles (Micro-MAVs) require control approaches that enable safe operation where extreme limitations in embedded systems, such as energy, processing capability and memory, are present. Nonlinear model predictive control (NMPC) approaches can respect operational constraints in a safe manner. However, they are typically challenging to implement using embedded computers on-board of Micro-MAVs. Implementations of classic NMPC approaches rely on high-performance computers. In this work, we propose a fast nonlinear model predictive control approach that ensures the stabilization and control of Micro Multirotor Aerial Vehicles (Micro-MAVs). This aerial robotic system uses a low processing power board that relies solely on on-board sensors to localize itself, which makes it suitable for experiments in GPS-denied environments. The proposed approach has been verified in numerical simulations using processing capabilities that are available on Micro-MAVs.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/GA20-10280S" target="_blank" >GA20-10280S: Spolehlivé kompaktní skupiny miniaturních vzdušných robotů proměnného tvaru řízené senzorickým vnímáním</a><br>

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

6

Strana od-do

523-528

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

000612041300068