Accuracy Of Industrial Robots Research Articles

An active learning hybrid reliability method for positioning accuracy of industrial robots

Popsitioning accuracy is an important index for evaluating the capacity of industrial robots. As a mechanism with multi-degree of freedom, the uncertainties of industrial robots are diverse and analyzing the positioning accuracy reliability is time consuming. To improve computation efficiency, a new active learning method based on Kriging model is proposed for hybrid reliability analysis of positioning accuracy with random and interval variables. In this study, the updated samples were selected through U learning function in the vicinity of limit-state function. A new stopping criterion based on expected risk function was exploited to judge whether the accuracy of Kriging model is enough. Two numerical examples and one engineering example were provided to verify the efficiency and accuracy of the proposed method. The results indicate that the proposed method is accurate and efficient.

Positioning Accuracy Reliability of Industrial Robots Through Probability and Evidence Theories

Abstract The positioning accuracy of industrial robots has an important influence on the stability and accuracy of robotic motion, which is one of the important indexes to measure the performance of robots. At present, some probability theory based methods are used to evaluate the positioning accuracy reliability of industrial robots. In practical engineering, the precise probability distribution of some robot’s parameters cannot be obtained directly. This study first uses the aleatory-epistemic hybrid model to describe the uncertain parameters of industrial robots. Second, the uncertain parameters are considered to construct the kinematic equation of industrial robots. Third, a probability-evidence hybrid reliability analysis model of industrial robots is established. Finally, the reliability interval of industrial robots under different thresholds can be obtained. Compared with the traditional method, the reliability results of industrial robots obtained by this method is an interval, which can more objectively evaluate the kinematics reliability of industrial robots. In the example, the effectiveness of the proposed method is verified by a six degrees of freedom (6-DoF) industrial robot.

Study on Torsional Vibration of RV Reducer Based on Time-Varying Stiffness

The torsional vibration of RV reducer is the key factor affecting the positioning accuracy and trajectory accuracy of industrial robots. It is of great significance to study the torsional stiffness periodic fluctuation and parametric torsional vibration to improve the torsional vibration performance and transmission accuracy of RV reducer. Based on the torsional stiffness test device of RV reducer, the torsional stiffness is measured and the torsional stiffness curve with periodic fluctuation is obtained. The trigonometric function fitting and mathematical description of torsional stiffness curve are carried out, and the torsional vibration equation of RV reducer parameters is established. The parametric torsional vibration response of RV reducer is simulated by Runge–Kutta method, and the combined frequency characteristics and system stability are analyzed. The torsional vibration test device of RV reducer is developed to study the torsional stiffness fluctuation and torsional vibration fault. The torsional stiffness fluctuation of RV reducer can be divided into a short period and long period, corresponding to different manufacturing errors, and the mechanism of torsional stiffness fluctuation is found out. The frequency spectrum of torsional vibration under working condition is highly consistent with the simulated response spectrum, and the harmonic resonance interval obtained by frequency sweeping is close to the peak of the torsional vibration–speed curve, so the correctness of the established torsional vibration model is verified. Using the mechanism of RV reducer stiffness fluctuation to realize rapid diagnosis of defective parts of RV reducer has a strong engineering application value. The time-varying torsional stiffness of RV reducer will cause the phenomenon of parametric torsional vibration. The vibration response characteristic frequency is a linear combination of internal reference variation frequency and external excitation frequency. The parametric torsional vibration will cause the harmonic resonance of RV reducer and aggravate the torsional vibration. Therefore, it is of great engineering value to study the time-varying torsional stiffness and torsional vibration of RV reducer.

A coarse-to-fine framework for accurate positioning under uncertainties—from autonomous robot to human–robot system

Recently, with the growing trend of high-mix, low-volume manufacturing, the demand for better flexibility and autonomy without sacrificing the accuracy of industrial robots and human–robot systems has increased. In this paper, a framework based on a coarse-to-fine strategy for industrial robots and human–robot systems is proposed to push the bounds of machine autonomy and machine flexibility while simultaneously maintaining good accuracy and efficiency. Under the proposed framework, industrial robots and human operators are designated to conduct coarse global motion with the aim of implementing low-bandwidth planning-level intelligence. Simultaneously, fine local motion for tackling accumulated on-line uncertainties is realized by an add-on robotic module with the role of implementing high-bandwidth action-level intelligence. Consequently, the overall system for both applications provides good adaptability to uncertain work conditions, while concurrently realizing fast and accurate positioning. A contour following task in two dimensions, simulating simplified tasks in industrial applications (e.g., sealant application, inspection, welding), was implemented and evaluated by autonomous robot control and human–robot collaboration.

Variable Parameters Stiffness Identification and Modeling for Positional Compensation of Industrial Robots

Due to the weak stiffness of robot structure, the positional accuracy of industrial robots under load can hardly meet the application requirements of high-precision machining. Predicting and compensating errors by accurate stiffness modeling is an effective method to improve robot positional accuracy. Existing stiffness modeling methods use theoretical kinematic parameters and approximate the joint stiffness to a fixed value, so that the modeling accuracy is poor. Thus, this paper proposes a regular sampling point selection method by space gridding. Then, combining Levenberg-Marquardt kinematics parameter calibration and static joint stiffness identification methods, a comprehensive identification method is proposed to achieve simultaneous identifying of robot kinematics and stiffness parameters. Next, a variable parameter stiffness model could be established, according to the identification results in different workspaces. Finally, a model-based error prediction and compensation method is put forward through online sensing of external load. The error compensation is performed on a KR500 robot, and experimental results verified that the average value of absolute positional errors caused by external load, could be reduced by 44.61%, compared with the traditional compensation method.

A computational framework of kinematic accuracy reliability analysis for industrial robots

A new computational method to evaluate comprehensively the positional accuracy reliability for single coordinate, single point, multipoint and trajectory accuracy of industrial robots is proposed using the sparse grid numerical integration method and the saddlepoint approximation method. A kinematic error model of end-effector is constructed in three coordinate directions using the sparse grid numerical integration method considering uncertain parameters. The first-four order moments and the covariance matrix for three coordinates of the end-effector are calculated by extended Gauss–Hermite integration nodes and corresponding weights. The eigen-decomposition is conducted to transform the interdependent coordinates into independent standard normal variables. An equivalent extreme value distribution of response is applied to assess the reliability of kinematic accuracy. The probability density function and probability of failure for extreme value distribution are then derived through the saddlepoint approximation method. Four examples are given to demonstrate the effectiveness of the proposed method.

Research of accuracy of industrial robot at work as part of flexible machining cells

In this paper, the factors affecting the accuracy of an industrial robot with an articulated kinematic as part of flexible production modules were analyzed. The accuracy of the circular movements of the robot gripper depending on the position in the working area and the load applied to the robot. A method for measuring stiffness using a laser interferometer and optics for measuring straightness is proposed. According to the results of the experiments, the types of errors were determined, causing the greatest error in the accuracy of the industrial robot movements. Recommendations on the need to measure certain types of errors when setting up flexible production modules are given.

Examination of industrial robot performance parameters utilizing machine tool diagnostic methods

The article discusses the possibility to identify changes in robot accuracy based on deformation of the circular path measured by the Renishaw Ballbar system. The research method utilizes correlation between industrial robot accuracy and precision of method used for the so-called calibration process. The presented experiments consist of two basic parts. The first is positional analysis with a simulation model of the robot in Creo Parametric 4.0. The second part describe practical measurements using the Renishaw Ballbar QC20-W and the Renishaw XL-80 laser interferometer. The results of the experiments confirm that Renishaw Ballbar can be used to quickly and simply identify occurrence of changes in the condition of an industrial robot.

A Practical Method to Improve Absolute Positioning Accuracy of Industrial Robot

Industrial robots had been wildly used in modern factory. While the high repeatability of industrial robots can address most of need of process, their low absolute positioning ability cannot reach the demands of some high precision tasks. An example is if the action of the robot relies on the real-time sampled data rather than the simulated data. The low absolute positioning ability of the robot will cause working performance far different away from expectation. For improving the absolute positioning accuracy as long as compile with the programs of automation integration projects, a practical general compensation method has been advanced. Our method also can be a compensation frame which can absorb new better model in the future. One application of this method in a project verifies the achievement of this method.

Plane kinematic calibration method for industrial robot based on dynamic measurement of double ball bar

A new calibration method is proposed to improve the circular plane kinematic accuracy of industrial robot by using dynamic measurement of double ball bar (DBB). The kinematic model of robot is established by the MDH (Modified Denavit-Hartenberg) method. The error mapping relationship between the motion error of end-effector and the kinematic parameter error of each axis is calculated through the Jacobian iterative method. In order to identify the validity of the MDH parameter errors, distance errors and angle errors of each joint axis were simulated by three orders of magnitude respectively. After multiple iterations, the average value of kinematic error modulus of end-effector was reduced to nanometer range. Experiments were conducted on an industrial robot (EPSON C4 A901) in the working space of 180 mm × 490 mm. Due to the measuring radius of DBB, the working space was divided into 30 sub-planes to measure the roundness error before and after compensation. The average roundness error calibrated by the proposed method at multi-planes decreased about 21.4%, from 0.4637 mm to 0.3644 mm, while the standard deviation of roundness error was reduced from 0.0720 mm to 0.0656 mm. In addition, by comparing the results of positioning error measured by the laser interferometer before and after calibration, the range values of motion errors of end-effector were decreasing by 0.1033 mm and 0.0730 mm on the X and Y axes, respectively.

A positional error compensation method for industrial robots combining error similarity and radial basis function neural network

To solve the problem of low absolute position accuracy for industrial robots in application, a positional error compensation method combing error similarity and RBF neural networks is proposed. The positional errors experience error similarity when describing the degree of error similarity developed with the error model based on a robot kinematic model. The experimental semivariogram is fitted by using a set of robot joint angles and corresponding positional errors. The bandwidth of the RBF neural network is modified by using the parameter of semivariogram. Then, an RBF neural network is constructed to estimate the positional errors of the target positions. The estimated positional errors are used to modify the target position. The modified position is given to the robot controller. To verify the proposed method, a simulation study and experiments are respectively carried out with a simulated robot and a KUKA KR210 industrial robot. The experimental results show that, after compensation, the average residual positional error is reduced by 91.99% from 1.361 mm to 0.109 mm and the maximum residual positional error is reduced by 85.41% from 1.741 mm to 0.254 mm. In addition, the proposed method can enhance the absolute position accuracy of industrial robots.

A Moment Approach to Positioning Accuracy Reliability Analysis for Industrial Robots

The uncertain variables of the link dimensions and joint clearances, whose deviation is caused by manufacturing and assembling errors, have a considerable influence on the positioning accuracy of industrial robots. Understanding how these uncertain variables affect the positioning accuracy of industrial robots is very important to select appropriate parameters during design process. In this paper, the positioning accuracy reliability of industrial robots is analyzed considering the influence of uncertain variables. First, the kinematic models of industrial robots are established based on the Denavit–Hartenberg method, in which the link lengths and joint rotation angles are treated as uncertain variables. Second, the Sobol’ method is used to analyze the sensitivity of uncertain variables for the positioning accuracy of industrial robots, by which the sensitive variables are determined to perform the reliability analysis. Finally, in view of the sensitive variables, the first-four order moments and probability density function of the manipulator's positioning point are assessed by the point estimation method (PEM) in three examples. The Monte Carlo simulation method, the maximum entropy problem with fractional order moments (maximum entropy problem with fractional order moments method (ME-FM) method), and the experimental method are also performed as comparative methods. All the results demonstrate that the proposed PEM has a higher accuracy and efficiency to assess the positioning accuracy reliability of industrial robots.

Improving the Absolute Accuracy by Online Interpolation Technique of Industrial Robots

This paper describes a novel method to improve the accuracy of industrial robot by calibration technique. Robot calibration is broadly classified into model-based and modeless techniques. In this paper, a modeless technique capable of interpolating the deviation along the Z-axis is defined which doesn’t consider any kinematic model, instead adapts interpolation method to compensate errors. The robot’s deviation is measured with a laser tracker and the deviation controlling parameters are calculated. The controlling parameters interpolate the deviation and with an online compensation program this deviation is compensated in real time scenario. This modeless technique is experimentally tested and it demonstrates a substantial improvement in the accuracy of the robot.

Industrial Robot Accuracy Degradation Monitoring and Quick Health Assessment

Robot accuracy degradation sensing, monitoring, and assessment are critical activities in many industrial robot applications, especially when it comes to the high accuracy operations which may include welding, material removal, robotic drilling, and robot riveting. The degradation of robot tool center accuracy can increase the likelihood of unexpected shutdowns and decrease manufacturing quality and production efficiency. The development of monitoring, diagnostic and prognostic (collectively known as prognostics and health management (PHM)) technologies can aid manufacturers in maintaining the performance of robot systems. PHM can provide the techniques and tools to support the specification of a robot’s present and future health state and optimization of maintenance strategies. This paper presents the robotic PHM research and the development of a quick health assessment at the U.S. National Institute of Standards and Technology (NIST). The research effort includes the advanced sensing development to measure the robot tool center position and orientation; a test method to generate a robot motion plan; an advanced robot error model that handles the geometric/nongeometric errors and the uncertainties of the measurement system, and algorithms to process measured data to assess the robot’s accuracy degradation. The algorithm has no concept of the traditional derivative or gradient for algorithm converging. A use case is presented to demonstrate the feasibility of the methodology.

Investigation of positioning accuracy of industrial robots for robotic-based X-ray computed tomography

In this research work we investigated the accuracy of a standard industrial robot. We wanted to find out, how accurate an X-Ray Computed Tomography (CT) scan can be performed when using such a robot as a manipulator. The accuracy was measured using a laser-interferometer. The measured deviations were used to run an X-Ray simulation via Fraunhofer EZRT’s Scorpius X-Lab. Metrological analysis was performed as a measure for the quality of the simulated CT-scan. The metrological deviations reflect the feasible accuracy of a CT-scan in a real CT-setup.

Improving the Accuracy of Industrial Robots via Iterative Reference Trajectory Modification

In this paper, a novel repetitive control (RC) scheme is presented and discussed. The general framework is the control of repetitive tasks of robotic systems or, more in general, of automatic machines. The key idea of the proposed scheme consists in modifying the reference trajectory provided to the plant in order to compensate for external loads or unmodeled dynamics that cyclically affect it. By exploiting the fact that uniform B-spline trajectories can be generated by means of dynamic filters, the trajectory planning phase has been integrated within an RC scheme that is able to modify in real time the reference signal in order to nullify the tracking errors occurring at the desired via-points. Because of this mechanism, the control scheme is very suitable for the application to industrial plants with off-the-shelf, unmodifiable controllers. Experimental results obtained with a standard industrial manipulator both in joint space and in workspace show the effectiveness of the proposed method.

Constructive methods to reduce thermal influences on the accuracy of industrial robots

Abstract Due to their kinematics and their mobility, industrial robot systems offer a flexible, adaptable basis. An influencing variable, which is particularly relevant for processes with long process times, is the thermal heating and the associated thermal drift of the tool center point. The maximum deviation from the actual nominal position can reach up to 1.5 mm. To counteract these displacements, a cooling strategy or a targeted preheating can be installed. Both possibilities were evaluated under constructive, energetic and economic aspects and implemented on at least one axis of an industrial robot. Furthermore, a structural thermal decoupling and optimized design of the respective components were carried out. The results can help to reduce the influence of thermal heating and the associated thermal drift of the TCP by structural support without using cost-intensive measures with additional hardware and software on external computers for compensating the errors.

Kinematic calibration for industrial robots using articulated arm coordinate machines

To improve the position accuracy of industrial robots, a novel kinematic model and calibration method using articulated arm coordinate machines (AACMM) is proposed in this paper. The end of the industrial robot is connected to the probe of an AACMM, thus forming a closed kinematic chain. The coordinate systems of the double arms were established, based on which the mapping of the joint angles and the position of the end were derived as well as the nominal value of the kinematic parameters of the industrial robot. A two-step search method was presented for kinematic parameter identification of the industrial robot. The identified kinematic parameters were used to compensate the errors of the nominal kinematic parameters in the controller of the industrial robot. Experiments were conducted to verify the calibration method, which show that after calibration, the average position errors of the industrial robot were decreased greatly.

Online pose correction of an industrial robot using an optical coordinate measure machine system

In this article, a dynamic pose correction scheme is proposed to enhance the pose accuracy of industrial robots. The dynamic pose correction scheme uses the dynamic pose measurements as feedback to accurately guide the robot end-effector to the desired pose. The pose is measured online with an optical coordinate measure machine, that is, C-Track 780 from Creaform. A root mean square method is proposed to filter the noise from the pose measurements. The dynamic pose correction scheme adopts proportional-integral-derivaitve controller and generates commands to the FANUC robot controller. The developed dynamic pose correction scheme has been tested on two industrial robots, FANUC LR Mate 200iC and FANUC M20iA. The experimental results on both robots demonstrate that the robots can reach the desired pose with an accuracy of ±0.050 mm for position and ±0.050° for orientation. As a result, the developed pose correction can make the industrial robots meet higher accuracy requirement in the applications such as riveting, drilling, and spot welding.

A spatial vector projection based error sensitivity analysis method for industrial robots

Precision design is an important approach to guarantee the accuracy of industrial robots, where error sensitivity analysis lays a vital foundation. Intuitively, if the pose error vector caused by one error component is nearly perpendicular to the sum vector that is caused by all error sources, this error component will have little influence on the accuracy of end-effector even though its norm is large. Unimportant errors may unreasonably be regarded as vital errors when their direction characteristics are ignored. In this paper, the local sensitivity index (LSI) is defined based on the projection theory of spatial vector to evaluate the contribution of an error component in a definite pose. Both the direction and norm characteristics of pose error vector are considered in the novel definition of LSI, which is quite different from the previous researches. According to the definition of expectation and variance, the average sensitivity indices (ASI) and variance sensitivity indices (VSI) of error sources are established. Finally, the precision design of a 6-DOF (degrees of freedom) industrial robot is conducted in numerical simulation based on the proposed error sensitivity analysis method. The results show that the pose accuracy of end-effector can greatly be increased by improving very few error components obtained via error sensitivity analysis. The proposed error sensitivity analysis method is quite effective, which can greatly improve precision design effects.