Pregled bibliografske jedinice broj: 1158950
Extended Kalman filter for payload state estimation utilizing aircraft inertial sensing
Extended Kalman filter for payload state estimation utilizing aircraft inertial sensing // Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)
Biograd na Moru, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2021. 9571038, 6 doi:10.1109/airpharo52252.2021.9571038 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1158950 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Extended Kalman filter for payload state estimation
utilizing aircraft inertial sensing
Autori
Prkačin, Vicko ; Palunko, Ivana ; Petrović, Ivan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2021
ISBN
978-1-6654-3390-1
Skup
Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)
Mjesto i datum
Biograd na Moru, Hrvatska, 04.10.2021. - 05.10.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
estimation ; suspended payload ; Extended Kalman Filter
Sažetak
In this paper we consider an aerial vehicle transporting a suspended payload and propose an Extended Kalman filter for payload state estimation. The filter is based on derived system dynamics and relies solely on onboard IMU measurements. Effectiveness of the method is verified in numerical simulations and experimentally.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
Ustanove:
Sveučilište u Dubrovniku
