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Puttybot: A sensorized robot for autonomous putty plastering.

Bibliographic Details
Title: Puttybot: A sensorized robot for autonomous putty plastering.
Authors: Liu, Zhao, Chen, Dayuan, Eldosoky, Mahmoud A., Ye, Zefeng, Jiang, Xin, Liu, Yunhui, Ge, Shuzhi Sam
Source: Journal of Field Robotics; Sep2024, Vol. 41 Issue 6, p1744-1764, 21p
Subject Terms: Convolutional neural networks, Impedance control, Autonomous robots, Systems design
Abstract: Plastering is dominated manually, exhibiting low levels of automation and inconsistent finished quality. A comprehensive review of literature indicates that extant plastering robots demonstrate a subpar performance when tasked with rectifying defects in the transition area. The limitations encompass a lack of capacity to independently evaluate the quality of work or perform remedial plastering procedures. To address this issue, this research describes the system design of the Puttybot and a paradigm of plastering to solve the stated problems. The Puttybot consists of a mobile chassis, a lift platform, and a macro/micromanipulator. The force‐controlled scraper parameters have been calibrated to dynamically modify their rigidity in response to the applied putty. This strategy utilizes convolutional neural networks to identify plastering defects and executes the plastering operation with force feedback. This paradigm's effectiveness was validated during an autonomous plastering trial wherein a large‐scale wall was processed without human involvement. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Field Robotics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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DbLabel: Complementary Index
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PubType: Academic Journal
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  Data: Puttybot: A sensorized robot for autonomous putty plastering.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Zhao%22">Liu, Zhao</searchLink><br /><searchLink fieldCode="AR" term="%22Chen%2C+Dayuan%22">Chen, Dayuan</searchLink><br /><searchLink fieldCode="AR" term="%22Eldosoky%2C+Mahmoud+A%2E%22">Eldosoky, Mahmoud A.</searchLink><br /><searchLink fieldCode="AR" term="%22Ye%2C+Zefeng%22">Ye, Zefeng</searchLink><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Xin%22">Jiang, Xin</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yunhui%22">Liu, Yunhui</searchLink><br /><searchLink fieldCode="AR" term="%22Ge%2C+Shuzhi+Sam%22">Ge, Shuzhi Sam</searchLink>
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  Data: Journal of Field Robotics; Sep2024, Vol. 41 Issue 6, p1744-1764, 21p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Convolutional+neural+networks%22">Convolutional neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Impedance+control%22">Impedance control</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomous+robots%22">Autonomous robots</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+design%22">Systems design</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Plastering is dominated manually, exhibiting low levels of automation and inconsistent finished quality. A comprehensive review of literature indicates that extant plastering robots demonstrate a subpar performance when tasked with rectifying defects in the transition area. The limitations encompass a lack of capacity to independently evaluate the quality of work or perform remedial plastering procedures. To address this issue, this research describes the system design of the Puttybot and a paradigm of plastering to solve the stated problems. The Puttybot consists of a mobile chassis, a lift platform, and a macro/micromanipulator. The force‐controlled scraper parameters have been calibrated to dynamically modify their rigidity in response to the applied putty. This strategy utilizes convolutional neural networks to identify plastering defects and executes the plastering operation with force feedback. This paradigm's effectiveness was validated during an autonomous plastering trial wherein a large‐scale wall was processed without human involvement. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Field Robotics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/rob.22351
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 1744
    Subjects:
      – SubjectFull: Convolutional neural networks
        Type: general
      – SubjectFull: Impedance control
        Type: general
      – SubjectFull: Autonomous robots
        Type: general
      – SubjectFull: Systems design
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      – TitleFull: Puttybot: A sensorized robot for autonomous putty plastering.
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            – D: 01
              M: 09
              Text: Sep2024
              Type: published
              Y: 2024
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