Monte Carlo Localization: Efficient Position Estimation for Mobile Robots

  title={Monte Carlo Localization: Efficient Position Estimation for Mobile Robots},
  author={Dieter Fox and Wolfram Burgard and Frank Dellaert and Sebastian Thrun},
This paper presents a new algorithm for mobile robot localization, called Monte Carlo Localization (MCL). MCL is a version of Markov localization, a family of probabilistic approaches that have recently been applied with great practical success. However, previous approaches were either computationally cumbersome (such as grid-based approaches that represent the state space by high-resolution 3D grids), or had to resort to extremely coarse-grained resolutions. Our approach is computationally… CONTINUE READING
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