In order to enable an autonomous mobile robot to travel over rough terrain, it necessitates the capability to detect self-position accurately even when the odometry errors are increased in traveling. The conventional method can keep high speed and precise localization using ICP algorithms or feature matching techniques. However, effects of steep changes of a mobile robot position are not considered when it travels over rough terrain. In this paper, we propose the method for efficient real-time 6D pose tracking using a rotating 2D laser scanner in traveling over rough terrain. For adaptation to steep changes of the position, weighted pointclouds are generated based on the angular and the linear velocity measured by sensors mounted on the robot. And the position and posture of the robot are sequentially optimized by the scan matching in increments of 10 scans. In indoor experiments, we evaluated accuracy of our method when the robot passes on rugged floor. As a result, our method was performed less than 0.078m RMS positional error in real time.
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