Probabilistic estimation of unmarked roads using radar

Juan I. Nieto, Andres Hernandez-Gutierrez, Eduardo Nebot

Resultado de la investigación

2 Citas (Scopus)

Resumen

This paper presents a probabilistic framework for unmarked roads estimation using radar sensors. The algorithm models the sensor likelihood function as a Gaussian mixture model. This sensor likelihood is used in a Bayesian approach to estimate the road edges probability distribution. A particle filter is used as the fusion mechanism to obtain posterior estimates of the road's parameters. The main applications of the approach presented are autonomous navigation and driver assistance. The use of radar permits the system to work even under difficult environmental conditions. Experimental results with data acquired in a mine environment are presented. By using a GPS mounted on the test vehicle, the algorithm outcome is registered with a satellite image of the experimental place. The registration allows to perform a qualitative analysis of the algorithm results. The results show the effectiveness of the algorithm presented.

Idioma originalEnglish
Páginas (desde-hasta)35-41
Número de páginas7
PublicaciónJournal of Physical Agents
Volumen4
N.º2
DOI
EstadoPublished - 1 ene 2010

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering

Huella Profundice en los temas de investigación de 'Probabilistic estimation of unmarked roads using radar'. En conjunto forman una huella única.

  • Citar esto