Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Fast Nonlinear Model Predictive Control for Very-Small Aerial Vehicles
Original language description
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.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA20-10280S" target="_blank" >GA20-10280S: Reliable sensing-driven compact groups of micro aerial robots with adaptive shapes</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
International Conference on Unmanned Aircraft Systems (ICUAS)
ISBN
978-1-7281-4278-4
ISSN
2373-6720
e-ISSN
2575-7296
Number of pages
6
Pages from-to
523-528
Publisher name
IEEE
Place of publication
Vancouver
Event location
Athens
Event date
Sep 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000612041300068

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