Long-term mapping and localization using feature stability histograms
We proposed a more complete Feature Stability Histogram model. The Feature Stability Histogram model is able to be used in current SLAM methods. Our approach is able to deal with long-term SLAM runs in dynamic environments. Our approach is able to filter out dynamic objects and to reduce the matching effort. Our approach is able to update the map in accordance with the changes observed.
long-term localization and mapping laser range finder particle filters omnidirectional vision