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Fusion of symbolic knowledge and uncertain information in robotics

✍ Scribed by Claudio Sossai; Paolo Bison; Gaetano Chemello

Publisher: John Wiley and Sons
Year: 2001
Tongue: English
Weight: 221 KB
Volume: 16
Category: Article
ISSN: 0884-8173
DOI: 10.1002/int.1061

No coin nor oath required. For personal study only.

✦ Synopsis

The interpretation of data coming from the real world may require different and often complementary uncertainty models: some are better described by possibility theory, others are intrinsically probabilistic. A logic for belief functions is introduced to axiomatize both semantics as special cases. As it properly extends classical logic, it also allows the fusion of data with different semantics and symbolic knowledge. The approach has been applied to the problem of mobile robot localization. For each place in the environment, a set of logical propositions allows the system to calculate the belief of the robot's presence as a function of the partial evidences provided by the individual sensors.

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