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Odometry is the most widely used method for estimation of the momentary position of mobile robots. It provides easily accessible real-time positioning information. However, with time, odometric localization accumulates errors in an unbounded fashion. This paper describes a way to decrease the odometry error by using a neutral network as a soft sensor. It makes a correction to the estimated orientation of the mobile robot, which is the most influenced on accumulated odometry errors. Trained neural network can be used instead of a gyro or a compass in some mobile robot applications.
Mobile Robots; Odometry; Neural Network
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