Data Fusion in the Navigation of Robots: Assessing Tools

Popular methods used for the navigation of robots simultaneously evaluate the localization of the robot and map the environment. Most of these methods are based on the well-known Kalman data fusion filter and its equivalents. Propositions for the evaluation and comparison of implementations of these techniques are presented.

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