Development of Macro-Micro Robot with a Compliant End Effector for Putty Applying

Chen, Dayuan; Li, Kang; Jiang, Xin; Liu, Yunhui

doi:10.1109/rcar49640.2020.9303321

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…For operation in limited space, a position control method for redundant manipulator is utilized. The comprehensive kinetic model and its solution have been elaborated upon in the work by Chen et al (2020).…”

Section: Rps Wmentioning

confidence: 99%

Puttybot: A sensorized robot for autonomous putty plastering

Liu,

Chen,

Eldosoky

et al. 2024

Journal of Field Robotics

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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.

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Section: Rps Wmentioning

confidence: 99%

Puttybot: A sensorized robot for autonomous putty plastering

Liu,

Chen,

Eldosoky

et al. 2024

Journal of Field Robotics

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Position Control Of the Macro/micro Manipulatormentioning

confidence: 99%

Puttybot - A sensorized robot for autonomous putty plastering

Liu,

Chen,

Eldosoky

et al. 2023

Preprint

View full text Add to dashboard Cite

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 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, lift platform, and a macro/micro manipulator. 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.

show abstract