Momentum-Based Extended Kalman Filter for Thrust Estimation on Flying Multibody Robots

Effective control design of flying vehicles requires a reliable estimation of the propellers’ thrust forces to secure a successful flight. Direct measurements of thrust forces, however, are seldom available in practice and on-line thrust estimation usually follows from the application of fusion algorithms that process on-board sensor data. This letter proposes a framework for the estimation of the thrust intensities on flying multibody systems that are not equipped with sensors for direct thrust measurement. The key ingredient of the proposed framework is the so-called centroidal momentum of a multibody system, which combined with the propeller model. It enables the design of Extended Kalman Filters (EKF) for on-line thrust estimation. The presented approach tackles the additional complexity in thrust estimation due to the possibly large number of degrees of freedom of the system and uncertainties in the propeller model. For instance, a covariance scheduling approach based on the turbines RPM error is proposed to ensure a reliable estimation even in case of turbine failures. Simulations are presented to validate the proposed algorithm during robot flight. Moreover, an experimental setup is designed to evaluate the accuracy of the estimation algorithm using iRonCub, a jet-powered humanoid robot, while standing on the ground

Comportamento espectral dos solos na paisagem a partir de dados coletados por sensores terrestre e orbital Spectral response of soils in the landscape based on terrestrial and orbital data acquisition levels

Parte da variabilidade dos índices de produção agrícola está associada com as características do solo e da paisagem. Dessa forma, práticas de manejo, como a adubação, devem levar em consideração esta variabilidade. O sensoriamento remoto é uma ferramenta que pode fornecer, de maneira rápida, informações para o manejo do solo, pois relaciona a radiação eletromagnética com os atributos do solo. Assim, este trabalho teve como objetivo avaliar o comportamento espectral, em dois níveis de aquisição de dados (terrestre e orbital), de diferentes classes de solos ao longo de toposseqüências na região de São Carlos e Ibaté, SP. Para isso, amostras de terra georreferenciadas foram coletadas em 319 pontos, em três profundidades. Em seguida, obtiveram-se os dados radiométricos em laboratório, na faixa espectral entre 450 e 2.500 nm. Os mesmos locais amostrados na camada superficial, no campo, foram avaliados na imagem de satélite. A partir dos resultados obtidos, pode-se concluir que: (a) teores de areia grossa, argila e matéria orgânica, e cor tiveram relação com a reflectância dos solos; (b) ao longo das vertentes ocorrem variações nos dados espectrais dos solos; e (c) solos da mesma ordem taxonômica, porém com classes texturais diferentes, apresentam diferentes comportamentos espectrais, podendo ser discriminados por sensoriamento remoto.<br>Part of agricultural production index variability is associated with soil and landscape characteristics. Management practices such as fertilizer application should therefore take the soil spatial variability into account. Remote sensing is a tool that can provide faster information for soil management because it relates electromagnetic radiation with soil attributes. Thus, this study aimed at evaluating the spectral response, at two data acquisition levels (terrestrial and orbital), of different soil classes across toposequences in the region of São Carlos and Ibaté, SP. For this purpose, georeferenced soil samples were collected at 319 points and three depths, and radiometric data were obtained in the laboratory using a spectroradiometer (spectral band 450-2500 nm). The same points sampled in the field in the surface layer were evaluated by the satellite image (ASTER). Based on the results it was possible to conclude that (a) coarse sand, clay, organic matter and color were strongly related with soil reflectance; (b) soil spectral data vary along the declivities; (c) soils of the same taxonomy order, but of different clay classes, have different spectral performances and can be discriminated by remote sensing