A neural approach to a sensor fusion problem

Our problem concerns the joint interpretation of UltraSonic and InfraRed measurements provided by a composite proximity sensor, in order to extract geometrical and morphological features of a at target. Neural networks are applied here both for modeling and for classi cation purposes. Physical knowledge of the sensing modalities helps in simplifying the network structure, in order to minimize its complexity, save computing time and make the system suitable for real time applications.

• Type: Conference
• Year: 1998
• Where: ESANN
• Authors: Valentina Colla, Mirko Sgarbi, Leonardo Maria Reyneri, Angelo M. Sabatini
• Keywords: Classi Cation, Composite Proximity Sensor, ESANN 1998, ESANN 2007, InfraRed Measurements