車載３次元 LIDAR による広域地図作成と基盤地図情報の道路に着目したグラフベース最適化手法

抄録

The paper presents a method to generate a large-scale 3D fundamental map from a running vehicle. As an easy-to-use approach for frequent updates, we propose a system to utilize Simultaneous Localization and Mapping (SLAM) which is robot mapping technology. In traditional methods, a special machine or many manual operations cause higher mapping costs. Existing Mobile mapping Method (MMS) requires manual anchoring points measurement for accuracy assurance. To solve the problem, we propose a 3D map optimization method by using road information of the standard map issued by The Geospatial Information Authority of Japan. Experimental results of on-vehicle 3D LIDAR observation show that the proposed system could correct the cumulative distortion of SLAM results and automatically generates large-scale 3D map assuring reference accuracy.