Markov Localization for Mobile Robots in Dynamic Environments

@article{Burgard1999MarkovLF,
  title={Markov Localization for Mobile Robots in Dynamic Environments},
  author={Wolfram Burgard and Dieter Fox and Sebastian Thrun},
  journal={ArXiv},
  year={1999},
  volume={abs/1106.0222}
}
Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate… 
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1,037 Citations
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1,037 Citations

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References

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  • W. BurgardAndrcas DerrD. FoxA. Cremers
  • Computer Science
    Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190)
  • 1998
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