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Adaptive sensor models

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3 Author(s)
J. W. M. van Dam ; Fac. of Math., Amsterdam Univ., Netherlands ; B. J. A. Krose ; F. C. A. Groen

In this paper we consider the conversion of sensor data to a probabilistic representation of the environment (occupancy grid). We introduce a neural network which learns these conversions. The conversion of sensor data remains adaptive to changes in either the sensor or its environment. To place this work in a broader context we describe the architecture of our sensor data fusion system in which these conversions are applied. We also introduce the PDOP: a rule for fusing occupancy grids in this system

Published in:

Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on

Date of Conference:

8-11 Dec 1996