論文

2020年

Attachable Sensor Boxes to Visualize Backhoe Motion

2020 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII)
  • Kento Yamada
  • Kazunori Ohno
  • Naoto Miyamoto
  • Taro Suzuki
  • Shotaro Kojima
  • Ranulfo Plutarco Bezerra Neto
  • Takahiro Suzuki
  • Keiji Nagatani
  • Yukinori Shibata
  • Kimitaka Asano
  • Tomohiro Komatsu
  • Satoshi Tadokoro
  • 全て表示

開始ページ
706
終了ページ
711
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
出版者・発行元
IEEE

Sensing position and orientation of construction vehicle is an important issue for automation of construction process. We aim to develop sensing and visualization technologies for construction vehicles. Our target construction vehicle is backhoes. Construction vehicles are usually rented in construction fields. However, construction vehicles that can be rented do not have the sensing function. It is too hard to obtain backhoe position and manipulator pose without sensing information. This paper proposes an attachable sensor box that can measure backhoe position and orientation and the manipulator pose. The sensor boxes can be attached on backhoe metal surface by magnetic force without any additional manufacturing on the construction vehicle surface. By using Wi-Fi communication and mobile battery the sensor box can be easily attached on large-size backhoe without wiring. After the work is done, it is easily detached by changing magnetic force power. At loading and scooping motion, backhoe arm and boom have large force exceeding 16 G. To attach the sensor boxes to the arm and boom, we designed an additional magnetic frame that can generate force of 1960 N. The sensor boxes were firmly attached to each joint and prevented to drop by any force from backhoes movement. We also measured the behavior of the backhoe in loading works in hot conditions over 30 degrees C and visualized backhoe pose and tip manipulator position.

リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000565648500124&DestApp=WOS_CPL
ID情報
  • ISSN : 2474-2317
  • Web of Science ID : WOS:000565648500124

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