A qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration

Valquiria Fenelon Pereira, Fabio Gagliardi Cozman, Paulo Eduardo Santos, Murilo Fernandes Martins

Resultado de la investigación: Contribución a una conferenciaArtículo de conferencia

4 Citas (Scopus)

Resumen

Typically, the spatial features of a robot's environment are specified using metric coordinates, and well-known mobile robot localisation techniques are used to track the exact robot position. In this paper, a qualitative-probabilistic approach is proposed to address the problem of mobile robot localisation. This approach combines a recently proposed logic theory called Perceptual Qualitative Reasoning about Shadows (PQRS) with a Bayesian filter. The approach herein proposed was systematically evaluated through experiments using a mobile robot in a real environment, where the sequential prediction and measurement steps of the Bayesian filter are used to both self-localisation and self-calibration of the robot's vision system from the observation of object's and their shadows. The results demonstrate that the qualitative-probabilistic approach effectively improves the accuracy of robot localisation, keeping the vision system well calibrated so that shadows can be properly detected. © 2013 IEEE.
Idioma originalInglés estadounidense
Páginas157-162
Número de páginas6
DOI
EstadoPublicada - 1 ene 2013
Publicado de forma externa
EventoProceedings - 2013 Brazilian Conference on Intelligent Systems, BRACIS 2013 -
Duración: 1 ene 2013 → …

Conferencia

ConferenciaProceedings - 2013 Brazilian Conference on Intelligent Systems, BRACIS 2013
Período1/01/13 → …

Huella Profundice en los temas de investigación de 'A qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration'. En conjunto forman una huella única.

  • Citar esto

    Pereira, V. F., Cozman, F. G., Santos, P. E., & Martins, M. F. (2013). A qualitative-probabilistic approach to autonomous mobile robot self localisation and self vision calibration. 157-162. Papel presentado en Proceedings - 2013 Brazilian Conference on Intelligent Systems, BRACIS 2013, . https://doi.org/10.1109/BRACIS.2013.34