An Uncertainty Propagation Architecture for the Localization Problem
Abstract
In this article, a dynamic localization method based on multi-target tracking is presented. The originality of this method is its capability to manage and propagate uncertainties during the localization process. This multi-level uncertainty propagation stage is based on the use of the Dempster-Shafer theory. The perception system we use is composed of an omnidirectional vision system and a panoramic range finder. It enables to treat complementary and redundant data and thus to construct a robust sensorial model which integrates an important number of significant primitives. Based on this model, we treat the problem of maintaining a matching and propagating uncertainties on each matched primitive in order to obtain a global uncertainty about the robot configuration.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2002
- Accession Number
- ADA520444
Entities
People
- Arnaud Clerentin
- Cyril Cauchois
- Eric Brassart
- Laurent Delahoche