Robust view matching-based Markov localization in outdoor environments

— This paper describes a view-based localization method in outdoor environments. An important issue in viewbased localization is to cope with the change of object views due to changes of weather and seasons. We have developed a two-stage SVM-based localization method which exhibits a high localization performance with few parameter tunings. In this paper, we extend the method in the following two ways: (1) adding new object models and visual features to deal with various urban scenes and (2) introducing a Markov localization strategy to utilize the history of movements. The new method can achieve a 100% localization performance in an urban route under a wide variety of conditions. The comparison with local feature-based methods is also discussed.

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Jun Miura, Koshiro Yamamoto
• Keywords: IROS 2008, Localization Method, Localization Performance, Robotics, View-based Localization Method