Positioning Error Compensation for Industrial Robots Based on Stiffness Modelling

Li, Yingjie; Gao, Guanbin; Liu, Fei

doi:10.1155/2020/8850751

Cited by 8 publications

(4 citation statements)

References 33 publications

(45 reference statements)

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“…Оскільки при роботі з певним роботом, його структура вже визначена, а параметри також вже зберігаються у внутрішньому контролері робота, при цьому контролер виконуватиме обчислення, щоб керувати тілом робота за цими попередньо збереженими параметрами [11]. Це процес виконання обчислень на основі внутрішніх параметрів (IPBC).…”

Section: керування на основі внутрішніх та точних параметрівunclassified

Compensation of Robot-Manipulator Positioning Errors in Work Space of Technological Equipment

Sokolova¹,

Visloukh²,

Antoniuk³

et al. 2022

Bull. Kyiv Polytech. Inst. Ser. Instrum. Mak.

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Industrial robots are widely used in modern enterprises. Although high repeatability of industrial robots can satisfy most process needs, their low absolute positioning accuracy in the workspace cannot meet the requirements of some high-precision tasks. An example, is that the action of a robot relies on real-time sample data rather than simulated data. The low absolute robot’s accuracy to positioning leads to the fact that work productivity is significantly different from what is expected. Therefore, the purpose of this paper is to analyze the developed program to increase the accuracy of robot-manipulator’s positioning in real time under the compilation with the programs of integration automation projects. The paper considers the deformation of the links, which is one of the robot manipulator’s production errors. The effect of applied forces on the connections and links can affect the deformation of the robot posture in different ways, and these changes are difficult to account for using linear algebra, so recently the demand for "offline programming" has increased, which will allow you to simulate the work of a robot manipulator with a change in time and will have a reasonable price. Therefore, the application of artificial neural networks based on optimization algorithms to compensate for absolute error was considered. After analyzing the existing technical solutions, a genetic algorithm was chosen that satisfies the conditions of ease of implementation, clarity, lack of redundant calculations, flexibility to the data types used. The paper also presents a general scheme of algorithms for optimizing the parameters of artificial neural networks and an iterative process of finding optimal values of hyperparameters using a genetic algorithm. After choosing the modelling method and optimization algorithm, the developed algorithm on an open data set was tested. The obtained results showed an increase in accuracy from 22 to 77% (positioning accuracy without the use of compensation methods). Therefore, this article describes a method of increasing the absolute accuracy of positioning under the condition of compilation with programs of integration automation projects. The result is a program based on the above method.

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Section: керування на основі внутрішніх та точних параметрівunclassified

Compensation of Robot-Manipulator Positioning Errors in Work Space of Technological Equipment

Sokolova¹,

Visloukh²,

Antoniuk³

et al. 2022

Bull. Kyiv Polytech. Inst. Ser. Instrum. Mak.

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“…Boeing used IGPS to complete position error detection of the cabin's feature points and control the robot to position and adjust pose during the final assembly process of large airliners [3]. References [4][5][6] use the robot kinematic model calibration method to improve the absolute positioning accuracy, which is realized by analyzing various error sources caused by the robot in manufacturing and usage and establishing the corresponding robot kinematic error model. In [7][8][9], T-MAC, binocular camera, and laser tracker are used separately to realize the real-time measurement of the position of the robot's end or the target component, and a full closed-loop compensation system is constructed to guide the robot to reach the target position.…”

Section: Introductionmentioning

confidence: 99%

Automatic assembly of in-cabin components based on hybrid guidance of binocular vision and laser tracker

Zhang,

Wang,

Yang

et al. 2024

J. Phys.: Conf. Ser.

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In order to automate the assembly of a certain type of missile cabin interior components, a new assembly method with a mixture of binocular vision and laser tracker is proposed. The laser tracker is used to determine the coarse position and posture relationship between the cabin segment and the robot. The two binocular vision systems use skeleton extraction and hit-and-miss transformation to extract target cross-hatch features, perform pose fitting, and obtain the fine pose relationship between the target and the component. Twenty full-process simulations are performed on the CoppeliaSim platform. The results show that, with a pixel accuracy of 0.053 mm, the mean value of the position error of the assembly is 0.614 mm with a standard deviation of 0.270, and the mean value of the posture angle error of the assembly is -0.036° with a standard deviation of 0.178. This method realizes automatic grasp-release action and improved absolute positioning accuracy of the robot in the uncalibrated case and can meet the automation and precision needs of production in the final assembly plant.

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“…On one hand, when the drill bit touches the rigid, slippery, and steep cortical surfaces, drill skidding is likely to occur and the highly heterogeneous bone tissue may also cause the drill to deviate from the correct direction [ 3 ]. On the other hand, the insufficient stiffness of the robot can significantly reduce the positioning accuracy, which is a well-known issue in the field of robotic machining [ 8 , 9 ]. The two factors combine, causing the deviation of the drilling path, which may result in the damage of the end-effector as well as the surrounding tissue due to the high-speed rotation of the drill.…”

Section: Introductionmentioning

confidence: 99%

Force-Position Hybrid Compensation Control for Path Deviation in Robot-Assisted Bone Drilling

Li,

Zhong,

Yang

et al. 2023

Sensors

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Bone drilling is a common procedure in orthopedic surgery and is frequently attempted using robot-assisted techniques. However, drilling on rigid, slippery, and steep cortical surfaces, which are frequently encountered in robot-assisted operations due to limited workspace, can lead to tool path deviation. Path deviation can have significant impacts on positioning accuracy, hole quality, and surgical safety. In this paper, we consider the deformation of the tool and the robot as the main factors contributing to path deviation. To address this issue, we establish a multi-stage mechanistic model of tool–bone interaction and develop a stiffness model of the robot. Additionally, a joint stiffness identification method is proposed. To compensate for path deviation in robot-assisted bone drilling, a force-position hybrid compensation control framework is proposed based on the derived models and a compensation strategy of path prediction. Our experimental results validate the effectiveness of the proposed compensation control method. Specifically, the path deviation is significantly reduced by 56.6%, the force of the tool is reduced by 38.5%, and the hole quality is substantially improved. The proposed compensation control method based on a multi-stage mechanistic model and joint stiffness identification method can significantly improve the accuracy and safety of robot-assisted bone drilling.

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Positioning Error Compensation for Industrial Robots Based on Stiffness Modelling

Cited by 8 publications

References 33 publications

Compensation of Robot-Manipulator Positioning Errors in Work Space of Technological Equipment

Compensation of Robot-Manipulator Positioning Errors in Work Space of Technological Equipment

Automatic assembly of in-cabin components based on hybrid guidance of binocular vision and laser tracker

Force-Position Hybrid Compensation Control for Path Deviation in Robot-Assisted Bone Drilling

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