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A New Approach to Self-Localization for Mobile Robots Using Sensor Data Fusion

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Figure

Figure 1.rotational and translational displacements, estimated by dead reckoning. Robot’s kinematics, based on the values of
Figure 3. A local map extracted from a global occupancy grids map. Calibration of pose estimation, has led to some rotational and translational displacement in the extracted map
Figure 4 . Our proposed step-by-step algorithm of calibrated pose estimation for a mobile robot, while it is exploring and mapping the environment around itself
Figure 6. A photo of khepera and the environment, in our experiments.
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