YOLOを用いた人除去処理によるICP-SLAMの性能向上

抄録

In this paper, we propose a novel ICP-SLAM approach that can build robust map information even in indoor environments with people. In general, when a mobile robot constructs a map in an environment where there are people nearby, it is difficult to construct a map with high accuracy due to occlusion caused by people. Therefore, YOLO is utilized to detect people in image data and human removal process is applied to improve the accuracy of map information.