Use of Kalman filter and computational vision for the correction of uncertainties in the navigation of autonomous robots / Uso de filtro de Kalman e visão computacional para a correção de incertezas de navegação de robos autonomos

AUTOR(ES)
DATA DE PUBLICAÇÃO

2008

RESUMO

The work establishes a collection of procedures for image based navigation control of an autonomous robot. Intensity maps obtained from cameras are transformed in depth maps, which provide information about the robot s localization in an environment, comprised of distinct objects. A two wheeled, differential powered robot model is used, allowing the navigation process to combine double source information from the camera and odometry sensors. The Kalman filter technique is used in this information combination in order to yield optimal estimates of position of the robot, based on the camera and odometry information. Computational simulations are used to validate the image capture and processing, as well as the sensorial fusion technique, in a simplified bi-dimensional environment. The simulations are also useful in accessing the viability and robustness of the navigation process, in the presence of measurement uncertainties associated to the camera and odometry measurements.

ASSUNTO(S)

robos - sistemas de controle navegação de robos moveis navigations kalman vehicle autonomous veiculos autonomos robotic vision control filtragem de

ACESSO AO ARTIGO

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