%0 Book Section
%3 Penha_image.pdf
%4 sid.inpe.br/mtc-m21c/2018/07.18.16.21
%A Penha Neto, Gerson da,
%A Campos Velho, Haroldo Fraga de,
%A Shiguemori, Elcio Hideki,
%@secondarytype PRE LI
%B Integral methods in science and engineering
%C Brighton, UK
%D 2019
%E Constanda, Christian,
%E Harris, Paul,
%@secondarykey INPE--PRE/
%I Springer
%K Unmanned aerial vehicles, Kalman filter, artificial neural networks.
%P 321-342
%T Image processing for UAV autonomous navigation applying self-configuring neural network
%X Application and development of Unmanned Aerial Vehicles (UAV) have had a rapid growth. The flight control of these aircarfts can be performed remotely or autonomously. There are different strategies for the UAV autonomous navigation. The positioning estimation can be done by using inertial sensors and General Navigation Satellite Systems (GNSS). The use of the GNSS signal can present some difficulties: natural or not natural interference. An alternative for positioning adjustment is to use a data fusion from different sensors by a Kalman filter. A supervised artificial network (ANN) is trained to emulate the filter for reducing the computational effort. An automatic best topology for the neural network is obtained by minimizing a functional by a new meta-heurisc called Multi-Particle Collision Algorithm (MPCA). Our results show similar accuracy between the ANN and the Kalman filter, with better processing performance to the neural network.
%@area COMP
%@electronicmailaddress gerson.penha@inpe.br
%@electronicmailaddress haroldo.camposvelho@inpe.br
%@documentstage not transferred
%@group CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
%@group LABAC-COCTE-INPE-MCTIC-GOV-BR
%@isbn 978-3-030-16077-7
%@usergroup simone
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHC3
%@nexthigherunit 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPCW/3F2PHGS
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%2 sid.inpe.br/mtc-m21c/2018/07.18.16.21.06