IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2022i1p18-d1010659.html
   My bibliography  Save this article

Agricultural Robot under Solar Panels for Sowing, Pruning, and Harvesting in a Synecoculture Environment

Author

Listed:
  • Takuya Otani

    (Waseda Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Akira Itoh

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Hideki Mizukami

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Masatsugu Murakami

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Shunya Yoshida

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Kota Terae

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Taiga Tanaka

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Koki Masaya

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Shuntaro Aotake

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan
    Sony Computer Science Laboratories, Inc., Tokyo 141-0022, Japan)

  • Masatoshi Funabashi

    (Sony Computer Science Laboratories, Inc., Tokyo 141-0022, Japan)

  • Atsuo Takanishi

    (Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

Abstract

Currently, an agricultural method called Synecoculture TM has been receiving attention as a means for multiple crop production and recovering from environmental degradation; it helps in regreening the environment and establishing an augmented ecosystem with high biodiversity. In this method, several types of plants are grown densely, and their management relies mainly on manual labor, since conventional agricultural machines and robots cannot be applied in complex vegetation. To improve work efficiency and boost regreening by scaling-up Synecoculture, we developed a robot that can sow, prune, and harvest in dense and diverse vegetation that grows under solar panels, towards the achievement of compatibility between food and energy production on a large scale. We adopted a four-wheel mechanism with sufficient ability to move on uneven terrain, and a two orthogonal axes mechanism with adjusted tool positioning while performing management tasks. In the field experiment, the robot could move straight on shelving slopes and overcome obstacles, such as small steps and weeds, and succeeded in harvesting and weeding with human operation, using the tool maneuver mechanism based on the recognition of the field situation through camera image.

Suggested Citation

  • Takuya Otani & Akira Itoh & Hideki Mizukami & Masatsugu Murakami & Shunya Yoshida & Kota Terae & Taiga Tanaka & Koki Masaya & Shuntaro Aotake & Masatoshi Funabashi & Atsuo Takanishi, 2022. "Agricultural Robot under Solar Panels for Sowing, Pruning, and Harvesting in a Synecoculture Environment," Agriculture, MDPI, vol. 13(1), pages 1-22, December.
    • Handle: RePEc:gam:jagris:v:13:y:2022:i:1:p:18-:d:1010659
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/1/18/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/1/18/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kousaku Ohta & Tatsuya Kawaoka & Masatoshi Funabashi, 2020. "Secondary Metabolite Differences between Naturally Grown and Conventional Coarse Green Tea," Agriculture, MDPI, vol. 10(12), pages 1-23, December.
    2. Hui Li & Hu Liu & Jilei Zhou & Guojian Wei & Song Shi & Xiangcai Zhang & Rongfang Zhang & Huibin Zhu & Tengfei He, 2021. "Development and First Results of a No-Till Pneumatic Seeder for Maize Precise Sowing in Huang-Huai-Hai Plain of China," Agriculture, MDPI, vol. 11(10), pages 1-22, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huawei Yang & Yinzeng Liu & Shaowei Wang & Huixing Qu & Ning Li & Jie Wu & Yinfa Yan & Hongjian Zhang & Jinxing Wang & Jianfeng Qiu, 2023. "Improved Apple Fruit Target Recognition Method Based on YOLOv7 Model," Agriculture, MDPI, vol. 13(7), pages 1-21, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhenguo Zhang & Quanfeng Guo & Jin He & Minyi Zhao & Zhenyu Xing & Chao Zeng & Han Lin & Quanyu Wang, 2023. "Design and Experiment of Side-Shift Stubble Avoidance System for No-Till Wheat Seeder Based on Deviation-Perception Fusion Technology," Agriculture, MDPI, vol. 13(1), pages 1-18, January.
    2. Yunxiang Li & Caiyun Lu & Hongwen Li & Jin He & Qingjie Wang & Shenghai Huang & Zhen Gao & Panpan Yuan & Xuyang Wei & Huimin Zhan, 2022. "Design and Experiment of Spiral Discharge Anti-Blocking and Row-Sorting Device of Wheat No-Till Planter," Agriculture, MDPI, vol. 12(4), pages 1-18, March.
    3. Yunxiang Li & Caiyun Lu & Hongwen Li & Zhinan Wang & Zhen Gao & Xuyang Wei & Dong He, 2022. "Design and Experiment of Symmetrical Spiral Row-Sorting of the Straw Device Based on Kinematics Analysis," Agriculture, MDPI, vol. 12(7), pages 1-19, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2022:i:1:p:18-:d:1010659. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.