セッションID: 1A1-H04
会議情報
主催: 一般社団法人 日本機械学会
会議名: ロボティクス・メカトロニクス 講演会2019
開催日: 2019/06/05 - 2019/06/08
実生活空間の空間状態を理解した地図生成
詳細
主催: 一般社団法人 日本機械学会
会議名: ロボティクス・メカトロニクス 講演会2019
開催日: 2019/06/05 - 2019/06/08
In this paper, a robust mapping method considering the space status of real-life environment is proposed. A 2D map is generated by Simultaneous Localization and Mapping (SLAM) based on gmapping. The objects in the 3D space are recognized by deep learning method YOLO and reflected to the 2D map. The 2D map contains the 3D shape information of the objects so that the robot can plan its path more accurately without collisions with objects and entering the places where the spaces are potentially occupied by the objects (e.g. the spaces under desks).
