The use of mobile robots in everyday life is becoming increasingly important. For autonomous robots, accuracy and reliability of localization and navigation are crucial. Reliable information is required for a robot to function reliably, as the robot's actions depend on information about its environment. Better accuracy and reliability of information can be achieved by combining measurements from different sensors. This work deals with sensor fusion and the use of the obtained information in the localization of a mobile robot. Data collected by LIDAR and odometry are combined with a Kalman filter and used for localization, evaluating the results with an accurate indoor positioning system.
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