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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