Time-varying isobaric surface reconstruction and path planning for robotic grinding of weak-stiffness workpieces

Zhou, Pei; Zhao, Xingwei; Tao, Bo; Ding, Han

doi:10.1016/j.rcim.2020.101945

Cited by 19 publications

(3 citation statements)

References 38 publications

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“…In the paper from above [25], the TVIS as a virtual surface used to generate constant force in robotic grinding of weak-stiffness workpieces was defined, including contact trial (CT) and the reconstruction of the surface. The CT process measures the deformation and stiffness of the workpiece, and a TVIS mesh is constructed for grinding path planning.…”

Section: Grindingmentioning

confidence: 99%

“…Low stiffness of the workpiece also could significantly impact the overall machining process. In [25], a novel robotic grinding method was proposed to address the issue of serious deformations and vibration during the grinding of weak-stiffness machined parts. A TVIS was defined as a virtual surface to generate constant force during grinding, and a CT process was employed to actively sample the deformation and stiffness of the contact point using a force sensor.…”

Section: Curved Tool Path Complexity and Time-optimal Motion Planningmentioning

confidence: 99%

See 1 more Smart Citation

Industrial Robots in Mechanical Machining: Perspectives and Limitations

Makulavičius,

Petkevičius,

Rožėnė

et al. 2023

Robotics

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Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accuracy, and consistency in machining operations. However, robot implementation faces some limitations, such as a huge variety of materials and tools, low adaptability to environmental changes, flexibility issues, a complicated tool path preparation process, and challenges in quality control. Industrial robotics applications include cutting, milling, drilling, and grinding procedures on various materials, including metal, plastics, and wood. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. Some publications propose approaches for planning the robot’s posture or tool orientation. In contrast, others focus on optimizing machining parameters through the utilization of advanced control and computation, including machine learning methods with the integration of collected sensor data.

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Section: Grindingmentioning

confidence: 99%

Section: Curved Tool Path Complexity and Time-optimal Motion Planningmentioning

confidence: 99%

Industrial Robots in Mechanical Machining: Perspectives and Limitations

Makulavičius,

Petkevičius,

Rožėnė

et al. 2023

Robotics

View full text Add to dashboard Cite

show abstract

“…The industrial robot-workpiece interaction has an important role to perform tasks over complex surfaces such as painting [1][2][3] milling, 4 grinding, 5 laser cladding, 6 nondestructive examinations, 7,8 and robotic automated fiber placement applications. 9,10 The path planning can be classified into online and offline programming.…”

Section: Introductionmentioning

confidence: 99%

Novel surface optimization for trajectory reconstruction in industrial robot tasks

Funes-Lora

Vega-Alvarado

Rivera-Blas

et al. 2021

International Journal of Advanced Robotic Systems

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This study presents a novel algorithm implementation that optimizes manually recorded toolpaths with the use of a 3D-workpiece model to reduce manual error induced. The novel algorithm has three steps: workpiece declaration, manual toolpath declaration, and toolpath optimization using steepest descent algorithm. Steepest descent finds the surface route wherein the manually recorded toolpaths traverse over a 3D-workpiece surface. The optimized toolpaths were simulated and tested with an industrial robot showing minimal error compared to the desired optimized toolpaths. The results obtained from the presented implementation on three different trajectories demonstrate that the proposed methodology can reduce the manual error induced using as a reference the CAD-workpiece surface.

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Tool wear monitoring system in belt grinding based on image-processing techniques

Wang

Liu

2020

Int J Adv Manuf Technol

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Time-varying isobaric surface reconstruction and path planning for robotic grinding of weak-stiffness workpieces

Cited by 19 publications

References 38 publications

Industrial Robots in Mechanical Machining: Perspectives and Limitations

Industrial Robots in Mechanical Machining: Perspectives and Limitations

Novel surface optimization for trajectory reconstruction in industrial robot tasks

Tool wear monitoring system in belt grinding based on image-processing techniques

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