測量地図情報に基づく移動ロボットの自己位置推定法

抄録

For autonomous mobile robot navigation, localization is a fundamental technique. For this purpose, environmental maps are usually given beforehand by using SLAM. In stead of SLAM, we use an existing geographical map. Since road and building information are already included in the map, we focus on the scan data of the actual road surface and buildings in the environment obtained from a 3D LiDAR. In the map, MCL technique enables a robot to estimate the position. In the experiments, we show that the robot is able to autonomously move more stably through the localization with not only the scan data of the road surface, but also the ones of the buildings.