<title>Comparison of techniques for disparate sensor fusion</title>

摘要

The use of multiple disparate sensors such as range and visible is commonplace on most modern robotic platforms. Combination of evidence techniques which include Bayesian and Dempster-Shafer can be used to resolve some of the ambiguity in sensor outputs for scene segmentation purposes. This paper compares various versions of the Dempster-Shafer formalism and a neural network model for integration of disparate sensor outputs.