INVESTIGADORES
GIMENEZ ROMERO Javier Alejandro
congresos y reuniones científicas
Título:
Probabilistic mapping in agricultural environments using kernel estimators with recursive subsampling
Autor/es:
GIMENEZ ROMERO, JAVIER ALEJANDRO; TOSETTI SANTIAGO; SALINAS LUCIO; CARELLI, RICARDO
Lugar:
Mar del Plata
Reunión:
Workshop; XVII Workshop on Information Processing and Control (RPIC); 2017
Institución organizadora:
Facultad de Ingeniería de la Universidad Nacional de Mar del Plata
Resumen:
This work presents a non parametric probabilistic mapping based on kernel estimators which does not use grids.The proposed methodology characterizes the map with a cloud of points obtained from several observations of the environment. In order to maintain a bounded number of observations in memory, a recursive subsampling algorithm is proposed. The procedure is included in an SLAM, in order to localize the robot as well. An application example is the presented, where the proposed methodology is applied in an agricultural environment. Simulation and experimentation results are presented to validate the proposal.
