Positioning Accuracy Of Robot Research Articles

Small sample uncertainty evaluation of industrial robot position accuracy measurement based on grey model

The measurement of position accuracy of industrial robots has high complexity, and its uncertainty assessment is one of the important research topics. This study analyses the principle of measuring the position accuracy of industrial robots by laser tracker, the evaluation model of the measurement uncertainty of the position accuracy of industrial robots is established, and various factors affecting the measurement results are analysed, including industrial robot itself, the measurement instrument, the measurement personnel, the measurement strategy and the data processing method. There is a very small sample problem in the uncertainty evaluation process of the position accuracy of industrial robots. The literature and experiments show that the reliability of The Guide to the Expression of Uncertainty in Measurement is low under the condition of very small sample. In this study, an improved grey method is proposed to evaluate the uncertainty. The principle of the improved grey method is discussed in detail, and the general steps of the improved grey method are summarized. The experimental data prove that the standard deviation of very small sample calculated by the improved grey method has higher accuracy. Taking the position accuracy of an industrial robot measured by a laser tracker as an example, the improved grey method is successfully applied to the measurement uncertainty evaluation of the position accuracy of industrial robots.

Improvement of DC Motor Speed Control for Mobile Robot to Minimize Slip Phenomenon

Slip on the mobile robot has a significant impact on the maneuver and the accuracy of the mobile robot movement. The slip phenomenon occurs because of the loss of traction between the surface and the wheels due to the spontaneous acceleration or declaration application. This paper presents a method to improve DC motor performance by using slip control as an observer such that the slip phenomenon effect can be minimized. The performance that will be analyzed is the accuracy of motor speed and robot position accuracy when the robot is moving. The result shows that the Root Mean Squared Error (RMSE) for the motor speed performance that does not use slip control is 2.680, the system using slip control produces RMSE 1.3393. Regarding the robot position accuracy, the RMSE of the system that does not use slip control is 0.0379, the system using slip control is 0.0065.

Calibration Method Based on Models and Least-Squares Support Vector Regression Enhancing Robot Position Accuracy

The positioning accuracy of a robot directly affects the quality of its operations. In this study, a calibration method is proposed based on combining a model with least-squares support vector regression (LSSVR) to improve robot positioning accuracy. First, a geometric error model of the robot is established. Second, singular value decomposition (SVD) and physical model analysis method are employed to process the coupling parameters in the error model to improve the accuracy and efficiency of identification. Third, as nongeometric errors hinder the construction of an accurate and complete mathematical model and affect the residual positioning errors of the robot, LSSVR is used to compensate for the residual positioning errors caused by nongeometric errors. The proposed method thus improves the accuracy and robustness of finite sample estimation. Finally, an experiment is performed on an IRB1410 robot with a parallelogram mechanism. The maximum/mean positioning errors of the robot decrease from 2.0348/1.0978 mm to 0.1659/0.0733 mm, and the effectiveness of the proposed method is verified. The proposed method has higher prediction accuracy and stability for small samples than other methods.

MODEL BASED ROBOT CALIBRATION TECHNIQUE WITH CONSIDERATION OF JOINT COMPLIANCE

Robot accuracy plays an important role for robot based application in advanced industry. Especially, robot accuracy decreases because of structural deformation when robot carries heavy load. Identification of physical robot parameters improves its accuracy by updating robot model parameters which are used in robot controller. This research presents identification technique of robot geometric parameters and its joint deformation joint angle. The target of the paper is comparison of two cases 1) only geometric calibration and 2) geometric and joint deformation angles calibration. Simulation calibration is performed on a Hyundai 800 robot which is designed for carrying heavy loads. The robot position accuracy after calibration demonstrates the effectiveness and correctness of the method.

Passive Friction Compensation Using a Nonlinear Disturbance Observer for Flexible Joint Robots with Joint Torque Measurements

The friction and ripple effects from motor and drive cause a major problem for the robot position accuracy, especially for robots with high gear ratio and for high-speed applications. In this paper we introduce a simple, effective, and practical method to compensate for joint friction of flexible joint robots with joint torque sensing, which is based on a nonlinear disturbance observer. This friction observer can increase the performance of the controlled robot system both in terms of the position accuracy and the dynamic behavior. The friction observer needs no friction model and its output corresponds to the low-pass filtered friction torque. Due to the link torque feedback the friction observer can compensate for both friction moment and external moment effects acting on the link. So it can be used not only for position control but also for interaction control, e.g., torque control or impedance control which have low control bandwidth and therefore are sensitive to ripple effects from motor and drive. In addition, its parameter design and parameter optimization are independent of the controller design so that it can be used for friction compensation in conjunction with different controllers designed for flexible joint robots. Furthermore, a passivity analysis is done for this observer-based friction compensation in consideration of Coulomb, viscose and Stribeck friction effects, which is independent of the regulation controller. In combining this friction observer with the state feedback controller \cite{Albu-Schaeffer2}, global asymptotic stability of the controlled system can be shown by using Lyapunov based convergence analysis. Experimental results with robots of the German Aerospace Center (DLR) validate the practical efficiency of the approach.

A new calibration method for enhancing robot position accuracy by combining a robot model–based identification approach and an artificial neural network–based error compensation technique

Robot position accuracy plays a very important role in advanced industrial applications. This article proposes a new method for enhancing robot position accuracy. In order to increase robot accuracy, the proposed method models and identifies determinable error sources, for instance, geometric errors and joint deflection errors. Because non-geometric error sources such as link compliance, gear backlash, and others are difficult to model correctly and completely, an artificial neural network is used for compensating for the robot position errors, which are caused by these non-geometric error sources. The proposed method is used for experimental calibration of an industrial Hyundai HH800 robot designed for carrying heavy loads. The robot position accuracy after calibration demonstrates the effectiveness and correctness of the method.

Robot calibration using a portable photogrammetry system

Abstract This work investigates the potential use of a commercially-available portable photogrammetry system (the MaxSHOT 3D) in industrial robot calibration. To demonstrate the effectiveness of this system, we take the approach of comparing the device with a laser tracker (the FARO laser tracker) by calibrating an industrial robot, with each device in turn, then comparing the obtained robot position accuracy after calibration. As the use of a portable photogrammetry system in robot calibration is uncommon, this paper presents how to proceed. It will cover the theory of robot calibration: the robot's forward and inverse kinematics, the elasto-geometrical model of the robot, the generation and ultimate selection of robot configurations to be measured, and the parameter identification. Furthermore, an experimental comparison of the laser tracker and the MaxSHOT 3D is described. The obtained results show that the FARO laser tracker ION performs slightly better: The absolute positional accuracy obtained with the laser tracker is 0.365 mm and 0.147 mm for the maximum and the mean position errors, respectively. Nevertheless, the results obtained by using the MaxSHOT 3D are almost as good as those obtained by using the laser tracker: 0.469 mm and 0.197 mm for the maximum and the mean position errors, respectively. Performances in distance accuracy, after calibration (i.e. maximum errors), are respectively 0.329 mm and 0.352 mm, for the laser tracker and the MaxSHOT 3D. However, as the validation measurements were acquired with the laser tracker, bias favors this device. Thus, we may conclude that the calibration performances of the two measurement devices are very similar.

A calibration method for enhancing robot accuracy through integration of an extended Kalman filter algorithm and an artificial neural network

Robot position accuracy plays an important role in advanced industrial applications. In this paper, a new calibration method for enhancing robot position accuracy is proposed. In order to improve robot accuracy, the method first models and identifies its geometric parameters using an extended Kalman filtering (EKF) algorithm. Because the non-geometric error sources (such as the link deflection errors, joint compliance errors, gear backlash, and so on) are either difficult or impossible to model correctly and completely, an artificial neural network (ANN) will be applied to compensate for these un-modeled errors. The combination of model-based identification of the robot geometric errors using EKF and a compensation technique using the ANN could be an effective solution for the correction of all robot error sources. In order to demonstrate the effectiveness and correctness of the proposed method, simulated and experimental studies are carried out on serial PUMA and HH800 manipulators, respectively. The enhanced position accuracy of the robots after calibration confirms the practical effectiveness and correctness of the method.

Comparison of the efficiency of five observability indices for robot calibration

Abstract The purpose of this work is to evaluate the efficiency of five observability indices commonly used in robot calibration. For illustrative purposes, the study is performed in the case of an actual five-bar parallel robot and another three-degrees-of-freedom planar parallel robot, which are modeled with twelve geometric parameters each. A two-degrees-of-freedom planar serial robot is also considered. For each of the observability indices, a simulation study is performed for one hundred robot units (i.e. one hundred different sets of errors imposed on the parameters), four different numbers of calibration configurations, and four different levels of measurement noise. Results show that, in the case of low levels of measurement noise, all five observability indices yield excellent improvement in robot position accuracy. The interest of choosing an appropriate observability index becomes evident for high levels of measurement noises, and the comparison of the robot accuracy obtained by using each observability index becomes interesting. The results show that there is an observability index, which can be considered as the best choice (i.e. it is the best index in the most cases of our simulated robots).

Compensation for Geometric Parameter Errors of a Picking Manipulator

In order to enhance position accuracy of robots, the precise error model is established by applying homogeneous matrix without any differential or partial derivatives required in other methods. An articulated picking manipulator with four-degree-of-freedom is taken as example to analyze the position accuracy affected by errors of geometric parameters (link length, link offset and twist angle). Furthermore, an error compensation algorithm based on error model and inverse kinematics is proposed and applied to the picking manipulator. Experimental simulation was carried out for verifying the feasibility of the presented algorithm, and results show that the maximum position errors in x, y, z axis have declined from 3.2369mm, 9.5583mm, 1.002mm to 0.1334mm, -0.0488mm, -0.001mm after compensation, which could greatly improve the position accuracy of the picking manipulator.

An automated robot arm system for small animal tissue biopsy under dual-image modality

The ability to non-invasively monitor cell biology in vivo is one of the most important goals of molecular imaging. Imaging procedures could be inter-subject performed repeatedly at different investigating stages; thereby need not sacrifice small animals during the entire study period. Thus, the ultimate goal of this study was to design a stereotactic image-guided system for small animals and integrated it with an automatic robot arm for in vivo tissue biopsy analysis. The system was composed of three main parts, including one small animal stereotactic frame, one imaging-fusion software and an automatic robot arm system. The system has been thoroughly evaluated with three components; the robot position accuracy was 0.05±0.02 mm, the image registration accuracy was 0.37±0.18 mm and the system integration was satisfactorily within 1.20±0.39 mm of error. From these results, the system demonstrated sufficient accuracy to guide the micro-injector from the planned delivery routes into practice. The entire system accuracy was limited by the image fusion and orientation procedures, due to its nature of the blurred PET imaging obtained from the small objects. The primary improvement is to acquire as higher resolution as possible the fused imaging for localizing the targets in the future.

Qualification of Standard Industrial Robots to Cope with Sophisticated Assembly Tasks

New fields of application such as low-tolerance laser welding, micro and precision assembly or measurement technology are to be achieved by standard industrial robots for higher economic efficiency. However actual implementation fails due to the temperaturedrift caused by time variable internal and external sources of heat. A compensation method for fast online-correction of the time variable, thermal robot behaviour is introduced. This method is based on measuring the temperature-caused deviations and subsequent compensation by software during operation. The presented results show that the temperature caused deviations are minimized to the level of the system inherent repeatability. Hence constant position accuracy of robots can be achieved.

A study of three robot calibration methods based on flat surfaces

Among the various calibration techniques proposed by researchers, three of them applied a similar algorithm of which the data collection was constrained on two-dimensional surfaces even though the kinematic calibration was designed for improving a robot's position accuracy in a three-dimensional workspace. In addition to introducing the hardware and calibration algorithms applied, this paper also presents a comparison of the three methods. The calibration results are based on equal quantities of experimental data.

Improvement of local position accuracy of robots for off-line programming

For the implementation of industrial robots in a CIM environment, it is necessary to be able to position their end effectors to an abstractly defined cartesian position with desired accuracy. In other words, it is necessary to find accurate actuator command values corresponding to given goal positions which are expressed with respect to a certain coordinate frame. If the teaching-by-doing method is used, very accurate actuator command values are obtained from transducer readings. For the case when the goal poitions are mathematically expressed, however, the actuator command values for the goal positions must be calculated using robot kinematics. It is, however, well known that the position errors in the order of 10mm is not unusual while many industrial goal position and the position where a robot is actually controlled. To reduce the position errors, many researchers proposed calibration methods which are based on robot kinematic identification. However, those methods are quite complex and require an accurate position measuring device. In this paper, a new method which does not require the accurate kinematic identification, is appropriatly altered based on the available encoder readings of the several reference frames. To demonstrate the simplicity and the effectiveness of the method, computer simulations as well as experimental studies are performed and their results are discussed.