The Bayes Filter
<p>You probably could ask why this is a big problem. After all, can't sensors in a robot help it calculate its configuration precisely? In an ideal case, yes. But sensor readings can often be wrong. Even some of the best sensors like laser scanners and lidars can suffer from errors like crosstalk (different beams interfering with each other), total reflection (at obstacles like glass), random measurements (not following any pattern), and maximum range errors (where the maximum range of the sensor is reached and no obstacle is detected). These errors can be visualized in the figure below, showing a typical 24-beam ultrasound scan. That is why it is necessary to develop an efficient framework to localize a system's belief accurately over time, considering that many measurements are wrong or erratic.</p>
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