Accuracy improvement of robotic machining based on robot’s structural properties

Gotlih, Janez; Karner, Timi; Gotlih, Karl; Brezočnik, Miran

doi:10.1007/s00170-020-05438-z

“…According to Equations (3)(4)(5)(6), in addition to analysis the deformation influence coefficient, reducing the deformation of the components which has weak stiffness is another way to improve the machining accuracy. A comparative experiment is designed that Thomson PC25 series linear electric cylinder is selected to replace the original BXTL150 electric cylinders, as shown in the Figure 7.…”

Section: Cooling Mode Nonementioning

confidence: 99%

“…Xu et al [4] designed a novel six degrees-of-freedom (DOF) hybrid kinematic machine for polishing. Janez et al [5] described an approach to improve the robot's accuracy based on its structural properties which considering manipulability, structural stiffness, structure inertial, damping ratios, and natural frequencies.…”

Section: Introductionmentioning

confidence: 99%

Improving Machining Accuracy for a Robotic Arm with Hybrid Kinematic Chains Based on Deformation Characteristics

Sun

¹

,

Wang

²

,

Huang

³

et al. 2021

Preprint

0

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The joint deformation has great influence on machining accuracy for a robotic arm. In this paper, the deformation characteristics of the robotic arm with hybrid kinematic chains is investigated in order to improve its machining accuracy. Firstly, the deformation model of the joints has been established based on the Strain energy method and Castigliano theorem according to the robot structure. Secondly, the deformation influence coefficient (DIC) is defined to investigate the deformation influence of main components on the end-effector, and the deformation characteristics are evaluated by the simulation. Finally, a small size robotic arm prototype is established and robotic drilling comparative experiments are conducted. The theoretical and experiment results show that the machining method can be selected according to the DIC, which the force can be applied to the components with better stiffness. On the other hand, the deformation of driving components can also be reduced when the DIC cannot be adjusted to meet the accuracy requirement.

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“…Xu et al [4] designed a novel six degrees-of-freedom (DOF) hybrid kinematic machine for polishing. Janez et al [5] described an approach to improve the robot's accuracy based on its structural properties which considering manipulability, structural stiffness, structure inertial, damping ratios, and natural frequencies.…”

Section: Introductionmentioning

confidence: 99%

Improving machining accuracy for a robotic arm with hybrid kinematic chains based on deformation characteristics

Sun

¹

,

Wang

²

,

Huang

³

et al. 2022

Int J Adv Manuf Technol

1

0

View full text Add to dashboard Cite

The joint deformation has great influence on machining accuracy for a robotic arm. In this paper, the deformation characteristics of the robotic arm with hybrid kinematic chains is investigated in order to improve its machining accuracy. Firstly, the deformation model of the joints has been established based on the Strain energy method and Castigliano theorem according to the robot structure. Secondly, the deformation influence coefficient (DIC) is defined to investigate the deformation influence of main components on the end-effector, and the deformation characteristics are evaluated by the simulation. Finally, a small size robotic arm prototype is established and robotic drilling comparative experiments are conducted. The theoretical and experiment results show that the machining method can be selected according to the DIC, which the force can be applied to the components with better stiffness. On the other hand, the deformation of driving components can also be reduced when the DIC cannot be adjusted to meet the accuracy requirement.

show abstract

“…To optimize the stiffness of the robot along a trajectory, the stiffness of the robot throughout the workspace must be known. The following two main methods have evolved to determine the stiffness of the robot: global and local [29]. The advantage of the global approach is the ability to capture nonlinear effects due to friction and transmission losses, while the disadvantage is that the model does not generalize well to the entire workspace of the robot.…”

Section: Introductionmentioning

confidence: 99%

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

Gotlih

¹

,

Brezočnik

²

,

Karner

³

2021

Applied Sciences

5

0

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Deburring is recognized as an ideal technology for robotic automation. However, since the low stiffness of the robot can affect the deburring quality and the performance of an industrial robot is generally inhomogeneous over its workspace, a cell setup must be found that allows the robot to track the toolpath with the desired performance. In this work, the problems of robotic deburring are addressed by integrating components commonly used in the machining industry. A rotary table is integrated with the robotic deburring cell to increase the effective reach of the robot and enable it to machine a large workpiece. A genetic algorithm (GA) is used to optimize the placement of the workpiece based on the stiffness of the robot, and a local minimizer is used to maximize the stiffness of the robot along the deburring toolpath. During cutting motions, small table rotations are allowed so that the robot maintains high stiffness, and during non-cutting motions, large table rotations are allowed to reposition the workpiece. The stiffness of the robot is modeled by an artificial neural network (ANN). The results confirm the need to optimize the cell setup, since many optimizers cannot track the toolpath, while for the successful optimizers, a performance imbalance occurs along the toolpath.

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Accuracy improvement of robotic machining based on robot’s structural properties

Cited by 24 publications

References 53 publications

Improving Machining Accuracy for a Robotic Arm with Hybrid Kinematic Chains Based on Deformation Characteristics

Improving Machining Accuracy for a Robotic Arm with Hybrid Kinematic Chains Based on Deformation Characteristics

Improving machining accuracy for a robotic arm with hybrid kinematic chains based on deformation characteristics

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

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