Locating the Fruit to Be Harvested and Estimating their Cut Positions from RGBD Images Acquired by a Camera Moved along a Fixed Path Using a Mask\nR-CNN Based Method

• Item type: SIG Technical Reports(1)
• 公開日: 2022-11-17
• タイトル: Locating the Fruit to Be Harvested and Estimating their Cut Positions from RGBD Images Acquired by a Camera Moved along a Fixed Path Using a Mask\nR-CNN Based Method
• タイトル / 言語: en
• タイトル: Locating the Fruit to Be Harvested and Estimating their Cut Positions from RGBD Images Acquired by a Camera Moved along a Fixed Path Using a Mask\nR-CNN Based Method
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Faculty of Science and Engineering, Waseda University
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属: Sony Computer Science Laboratories, Inc.
• 著者所属: Sony Computer Science Laboratories, Inc.,
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Faculty of Science and Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Dept. of Modern Mechanical Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Sony Computer Science Laboratories, Inc.
• 著者所属(英): en
• 著者所属(英): Sony Computer Science Laboratories, Inc.,
• 著者名: Wentao, Zhao; Jun, Ohya; Chanjin, Seo; Takuya, Otani; Taiga, Tanaka; Koki, Masaya; Atsuo, Takanishi; Shuntaro, Aotake; Masatoshi, Funabashi
• 著者名(英): Wentao, Zhao; Jun, Ohya; Chanjin, Seo; Takuya, Otani; Taiga, Tanaka; Koki, Masaya; Atsuo, Takanishi; Shuntaro, Aotake; Masatoshi, Funabashi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper proposes a Mask R-CNN[1] based method for locating fruits (tomatoes and yellow bell peppers, etc.) and estimating the cutting positions from RGBD images acquired by a camera moved along a fixed path. After getting mask results of all fruits and pedicels (cutting positions), the proposed method judges the matching relationship between the located fruit and pedicel according to the distance between fruit and pedicel. Experimental results show the proposed method effectively detects the cutting position of each fruit. The method is also robust in complex environments. In addition, it turns out that the fixed path strategy is valid for avoiding obstacles and reaching the pedicel and cutting position accurately. A high harvesting success rate was achieved in a Gazebo based simulated environment.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper proposes a Mask R-CNN[1] based method for locating fruits (tomatoes and yellow bell peppers, etc.) and estimating the cutting positions from RGBD images acquired by a camera moved along a fixed path. After getting mask results of all fruits and pedicels (cutting positions), the proposed method judges the matching relationship between the located fruit and pedicel according to the distance between fruit and pedicel. Experimental results show the proposed method effectively detects the cutting position of each fruit. The method is also robust in complex environments. In addition, it turns out that the fixed path strategy is valid for avoiding obstacles and reaching the pedicel and cutting position accurately. A high harvesting success rate was achieved in a Gazebo based simulated environment.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10438399
• 書誌情報: 研究報告オーディオビジュアル複合情報処理（AVM）; 巻 2022-AVM-119, 号 9, p. 1-6, 発行日 2022-11-17
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8582
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会