画像特徴点を利用したマップマッチングによる自己位置推定

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/12/02

タイトル(英語): Self-localization Estimate by Map Matching using Image Feature Points

著者名: 李　忠鍾（東洋大学大学院工学研究科），寺田　信幸（東洋大学理工学部），秋元　俊成（東洋大学理工学部）

著者名(英語): Chungjong Lee (Graduate School of Engineering, Toyo University), Nobuyuki Terada (Undergraduate school of science and engineering, Toyo University), Toshinari Akimoto (Undergraduate school of science and engineering, Toyo University)

キーワード: ロボットビジョン，ステレオカメラ，SURF，特徴点，自己位置推定　　robot vision，stereo camera，SURF，Feature-Point，Self-Localization

要約(英語): This paper presents a self-localization system using image feature points. Using image feature points in a self-localization system has its limitations in terms of processing time and angle variation. In order for the system to use image feature points, it needs to solve both the angle variation and processing time problems. The image feature points store three-dimensional information by using a stereo camera unit, which is constructed from a web camera. The web camera was used to reduce cost and improve general versatility, and a particle filter was used for improving the performance of the self-localization system. The system was constructed in two steps. First, a map was constructed using the image feature points. Second, a robot run by autonomous locomotion estimated its self-position using this map. The experiment was performed in environments both identical and not identical to the map environment. In the final result, the robot arrived at the goal, regardless of the environment condition.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.12 （2013） 特集：電気関係学会東海支部連合大会

本誌掲載ページ: 2243-2250 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/12/133_2243/_article/-char/ja/