Indexing Invariant Features for Topological Mapping and Localization
euRathlon/ARCAS Workshop on Field Robotics
We propose an appearance-based approach for topological visual mapping and localization using local invariant features. To optimize running times, matchings between the current image and previously visited places are determined using an index based on a set of randomized kd-trees. We use a discrete Bayes filter for predicting loop candidates, whose observation model is a novel approach based on an efficient matching scheme between features. We assess our approach with several datasets obtained from indoor and outdoor environments under different weather conditions.