Uncertainty

The representation and management of information and uncertainty is inherent in perception with real sensors in real environments. The partners have played a leading international role in this field over the past decade. Research in uncertainty will focus on:

1. Probabilistic sensor modelling incorporating full density models of the physics of observation and detection;
2. efficient Bayesian engines for the manipulation and management of different probability representations;
3. algorithms for compression, abstraction and refinement of probabilistic data, focusing particularly on the use of information measures.

These three areas represent a real departure from current methods and approaches in defining a fundamental basis for management of perceptual uncertainty. Uncertainty research will be led by Eduardo Nebot.