Set membership approach to the propagation of uncertain geometric information

An alternative approach for the propagation of uncertain geometric information, based on the ideas presented by J.R. Deller (IEEE ASSP Magazine, vol.6, p.4-20, Oct. 1989) and extended to deal with graphs of geometric constraints, is presented. This method avoids the independency assumption of the probabilistic approach. In this approach, when new sensory data are acquired, a set of strips is obtained, propagated, and fused to obtain the updated ellipsoids associated with each feature, Then, the hypothesis about the location of the involved geometric features can be easily updated. Inconsistencies are easily detected, resulting in fast rejection of erroneous data.<<ETX>>