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Selecting Landmarks for Localization in Natural Terrain
Clark F. Olson Autonomous Robots, 12(2):201-210, March 2002. Download (750 K) We describe techniques to optimally select landmarks for performing mobile robot localization by matching terrain maps. The method is based upon a maximum-likelihood robot localization algorithm that efficiently searches the space of possible robot positions. We use a sensor error model to estimate a probability distribution over the terrain expected to be seen from the current robot position. The estimated distribution is compared to a previously generated map of the terrain and the optimal landmark is selected by minimizing the predicted uncertainty in the localization. This approach has been applied to the generation of a sensor uncertainty field that can be used by the robot's planning component. Experiments indicate that landmark selection improves not only the localization uncertainty, but also the likelihood of success. Examples of landmark selection are given using real and synthetic data. |
