Multi-sensor fusion: a perspective

A survey of the state of the art in multisensor fusion is presented. Papers related to fusion have been surveyed and classified into six categories: scene segmentation, representation, 3-D shape, sensor modeling, autonomous robots, and object recognition. A number of fusion strategies have been employed to combine sensor outputs. These strategies range from simple set intersection, logical and operations, and heuristic production rules to more complex methods involving nonlinear least-squares fits and maximum-likelihood estimates. Sensor uncertainty has been modeled using Bayesian probabilities and support and plausibility involving the Dempster-Shafer formalism.<<ETX>>

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