A computational framework of kinematic accuracy reliability analysis for industrial robots

Wu, Jinhui; Zhang, Dequan; Liu, Jie; Jia, Xinyu; Han, Xu

doi:10.1016/j.apm.2020.01.005

Cited by 64 publications

(13 citation statements)

References 43 publications

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“…To ensure that the mechanism works properly, the motion error must be controlled to an acceptable level. However, with the growing complexity of modern mechanisms and their increasing applications in hightech scenarios, it is found that the quantification in equation (2) cannot comprehensively reflect the level of motion error for the mechanisms. The definition of the motion error in equation ( 2) is too general to reflect and address the key concerns of motion accuracy.…”

Section: Two Definitions Of Motion Errorsmentioning

confidence: 99%

Uncertainty analysis of motion error for mechanisms and Kriging-based solutions

Zhou

Zhao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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In this work, the issue of uncertainty analysis of motion errors for mechanisms is studied. First, two definitions of motion errors, that is, maximum error and accumulative error, are introduced to measure the motion accuracy in a comprehensive way. Then, the method for performing an uncertainty analysis of the two errors is discussed. For the maximum error, an analysis of the failure probability and the corresponding sensitivity analysis are carried out. For the accumulative error, the variance-based sensitivity is studied to quantify the contributions of input variables to the mechanism performance. A Kriging-based method is proposed to reduce the computational cost of the uncertainty analysis of motion errors. Finally, four examples including the classical four-bar mechanism and the landing gear mechanism for aeronautical purposes are studied with the proposed method. Discussions on the results show that the uncertainty analysis of motion errors can provide helpful information for mechanisms.

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Section: Two Definitions Of Motion Errorsmentioning

confidence: 99%

Uncertainty analysis of motion error for mechanisms and Kriging-based solutions

Zhou

Zhao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Due to the change of wind speed, change of pump power, and jet carrier movement, the actual distance between the water jet muzzle and the expected landing point will change. In addition, due to the backhaul error caused by the clearance between the meshing gears in the process of mechanical transmission, these errors will also affect the control accuracy of the water shooting robot [ 27 , 28 , 29 , 30 ]. Once the model established for the ideal environment is affected by these factors, there will be a gap between the predicted pitch angle and the required pitch angle, which means that the water jet cannot shoot the target accurately according to the predicted pitch angle.…”

Section: Related Workmentioning

confidence: 99%

Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot

Lin

et al. 2021

Sensors

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In this paper, an intelligent water shooting robot system for situations of carrier shake and target movement is designed, which uses a 2 DOF (degree of freedom) robot as an actuator, a photoelectric camera to detect and track the desired target, and a gyroscope to keep the robot’s body stable when it is mounted on the motion carriers. Particularly, for the accurate shooting of the designed system, an online tuning model of the water jet landing point based on the back-propagation algorithm was proposed. The model has two stages. In the first stage, the polyfit function of Matlab is used to fit a model that satisfies the law of jet motion in ideal conditions without interference. In the second stage, the model uses the back-propagation algorithm to update the parameters online according to the visual feedback of the landing point position. The model established by this method can dynamically eliminate the interference of external factors and realize precise on-target shooting. The simulation results show that the model can dynamically adjust the parameters according to the state relationship between the landing point and the desired target, which keeps the predicted pitch angle error within 0.1°. In the test on the actual platform, when the landing point is 0.5 m away from the position of the desired target, the model only needs 0.3 s to adjust the water jet to hit the target. Compared to the state-of-the-art method, GA-BP (genetic algorithm-back-propagation), the proposed method’s predicted pitch angle error is within 0.1 degree with 1/4 model parameters, while costing 1/7 forward propagation time and 1/200 back-propagation calculation time.

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“…To be more specific, it refers to the likelihood that an arbitrary discrete point on its terminal trajectory falls within a presupposed tolerance zone, the center of which is on the desired path [18][19][20]. Nevertheless, the true motion accuracy is difficult to estimate on account of the high correlation between discrete points at different times and the accumulation of failure rates over time.…”

Section: Introductionmentioning

confidence: 99%

Kinematic Reliability Analysis of a 7-DOF Redundant Robot

Ding

et al. 2022

Journal of Robotics

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The kinematic reliability of robots, defined as the probability that the end-effector falls inside the specified safe boundary, is of great significance in predicting the accuracy achieved in reality. This work selects the 7 degrees-of-freedom (7-DOF) redundant robot as an example to conduct reliability analysis by utilizing the envelope method against time-related issues in this work. Since variables in industrial robots are very small relative to their means, the motion error functions are commonly linearized by the first-order Taylor’s formula to simplify calculation, and the failure models in all directions and attitude angles are then established through the probability method over the entire input interval. As a result, the actual accuracy of the robot in each pose component will be displayed, instead of merely considering the position error like other scholars. The principle of the proposed method is to transform a time-dependent problem into a time-independent one with the help of the failure extreme points and endpoints, so as to enhance the operation efficiency under the premise of ensuring accuracy. Finally, the simulation results verify that the relative error of the envelope method is less than 6.0% compared with that of the Monte Carlo simulation method, and the computational efficiency is higher than that of the Monte Carlo method, which demonstrates that the envelope method has better comprehensive performance.

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A computational framework of kinematic accuracy reliability analysis for industrial robots

Cited by 64 publications

References 43 publications

Uncertainty analysis of motion error for mechanisms and Kriging-based solutions

Uncertainty analysis of motion error for mechanisms and Kriging-based solutions

Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot

Kinematic Reliability Analysis of a 7-DOF Redundant Robot

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