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'''Recursive Bayesian estimation''', also known as a '''Bayes filter''', is a general probabilistic approach for [[density estimation|estimating]] an unknown [[probability density function]] recursively over time using incoming measurements and a mathematical process model.
==In robotics==
A Bayes filter is an algorithm used in [[computer science]] for calculating the probabilities of multiple beliefs to allow a [[robot]] to infer its position and orientation. Essentially, Bayes filters allow robots to continuously update their most likely position within a coordinate system, based on the most recently acquired sensor data. This is a recursive algorithm. It consists of two parts: prediction and innovation. If the variables are linear and [[Normal Distribution|normally distributed]] the Bayes filter becomes equal to the [[Kalman filter]].
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