Probabilistic Sonar Scan Matching for Robust Localization.
Antoni Burguera, Yolanda Gonz´alez and Gabriel Oliver
Abstract:
This paper presents a probabilistic framework toperform scan matching localization using standard time-offlightultrasonic sensors. Probabilistic models of the sensors aswell as techniques to propagate the errors through the modelsare also presented and discussed. A method to estimate themost probable trajectory followed by the robot according tothe scan matching and odometry estimations is also presented.Thanks to that, accurate robot localization can be performedwithout the need of geometric constraints. The experimentsdemonstrate the robustness of our method even in the presenceof large amounts of noisy readings and odometric errors.
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