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The purpose of this paper is to improve the positioning accuracy of 6-Dof serial robot by the way of error compensation and sensitivity analysis.

In this paper, the Denavit–Hartenberg matrix is used to construct the kinematics models of the robot; the effects from individual joint and several joints on the end effector are estimated by simulation. Then, an error model based on joint clearance is proposed so that the positioning accuracy at any position of joints can be predicted for compensation. Through the simulation of the curve path, the validity of the error compensation model is verified. Finally, the experimental results show that the error compensation method can improve the positioning accuracy of a two joint exoskeleton robot by nearly 76.46%.

Through the analysis of joint error sensitivity, it is found that the first three joints, especially joint 2, contribute a lot to the positioning accuracy of the robot, which provides guidance for the accuracy allocation of the robot. In addition, this paper creatively puts forward the error model based on joint clearance, and the error compensation method which decouples the positioning accuracy into joint errors.

It provides a new idea for error modeling and error compensation of 6-Dof serial robot. Combining sensitivity analysis results with error compensation can effectively improve the positioning accuracy of the robot, and provide convenience for welding robot and other robots that need high positioning accuracy.

This paper aims to enhance the machining accuracy of hybrid robots by treating the moving platform as the first joint of a serial robot for direct position measurement and integrating external grating sensors with motor encoders for real-time error compensation.

Initially, a spherical coordinate system is established using one linear and two circular grating sensors. This system enables direct acquisition of the moving platform’s position in the hybrid robot. Subsequently, during the coarse interpolation stage, the motor command for the next interpolation point is dynamically updated using error data from external grating sensors and motor encoders. Finally, fuzzy proportional integral derivative (PID) control is applied to maintain robot stability post-compensation.

Experiments were conducted on the TriMule-600 hybrid robot. The results indicate that the following errors of the five grating sensors are reduced by 94%, 93%, 80%, 75% and 88% respectively, after compensation. Using the fourth drive joint as an example, it was verified that fuzzy adaptive PID control performs better than traditional PID control.

The proposed online error compensation strategy significantly enhances the positional accuracy of the robot end, thereby improving the actual processing quality of the workpiece.

This method presents a technique for achieving online error compensation in hybrid robots, which promotes the advancement of the manufacturing industry.

This paper proposes a cost-effective and practical method for online error compensation in hybrid robots using grating sensors, which contributes to the advancement of hybrid robot technology.

The purpose of this research is to extend the previous approach to software error compensation to fused deposition modeling (FDM) machines and explores the approach to apply compensation by correcting slice files.

In addition to applying the stereolithography (STL) file‐based compensation method from earlier research; a new approach using the slice file format to apply compensation is presented. Under this approach, the confounded effects of all errors in a FDM machine are mapped into a “virtual” parametric machine error model. A 3D artifact is built on the FDM machine and differences between its actual and nominal dimensions are used to estimate the coefficients of the error functions. A slice file compensation method is developed and tested on two types of parts as a means for further improving the error compensation for feature form error improvement. STL file compensation is also applied to a specific FDM 3000 machine and the results are compared with those of a specific SLA 250 machine.

The two compensation methods are compared. Although, the slice file compensation method theoretically allows higher compensation resolution, the actual machine control resolution of the FDM machine can be a limitation which makes the difference between STL compensation and slice file compensation indistinguishable. However, as the control resolution is increased, this method will make it possible to provide a higher degree of compensation.

Compensation method applied to slice file format is developed for FDM machines and its limitations are explored. Based on the experimental study, dimensional accuracy of parts is considerably improved by the software error compensation approach.

As manufacturing technology has developed, digital models from advanced measuring devices have been widely used in manufacturing sectors. To speed up the production cycle and reduce extra errors introduced in surface reconstruction processes, directly machining digital models in the polygonal stereolithographyformat has been considered as an effective approach in rapid digital manufacturing. In machining processes, Cutter Location (CL) data for numerical control (NC) machining is generated usually from an offset model. This model is created by offsetting each vertex of the original model along its vertex vector. However, this method has the drawback of overcut to the offset model. The purpose of this paper is to solve the overcut problem through an error compensation algorithm to the vertex offset model.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed and implemented an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. This error compensation method is verified through three polygonal models and the tool paths generated were used for a real part machining.

Based on the analysis of the vertex offset method and the offset model generated, the authors developed an error compensation method to correct the offset models and generated the accurate CL data for the subsequent machining process. The developed error compensation algorithm can effectively solve the overcut drawback of the vertex offset method.

The error compensation method to the vertex offset model is used for generating the CL data with the using of a ball-end cutter.

On the study of CL data generation for a STL model, most of the current studies are focused on the determination of the offset vectors of the vertexes. The offset distance is usually fixed to the radius of the cutter used. Thus, the overcut problem to the offset model is inevitable and has not been much studied. The authors propose an effective approach to compensate the insufficient distance of the offset vertex and solve the overcut problem.

The directly tool paths generation from a STL model can reduce the error of surface reconstruction and speed up the machining progress.

The authors investigate the overcut problem occurred in vertex offset for CL data generation and present a new error compensation algorithm for generating the CL data that can effectively solve the overcut problem.

The purpose of this paper is to propose a method for selecting the position and attitude trajectory of error measurement to improve the kinematic calibration efficiency of a one translational and two rotational (1T2R) parallel power head and to improve the error compensation effect by improving the properties of the error identification matrix.

First, a general mapping model between the endpoint synthesis error is established and each geometric error source. Second, a model for optimizing the position and attitude trajectory of error measurement based on sensitivity analysis results is proposed, providing a basis for optimizing the error measurement trajectory of the mechanism in the working space. Finally, distance error measurement information and principal component analysis (PCA) ideas are used to construct an error identification matrix. The robustness and compensation effect of the identification algorithm were verified by simulation and through experiments.

Through sensitivity analysis, it is found that the distribution of the sensitivity coefficient of each error source in the plane of the workspace can approximately represent its distribution in the workspace, and when the end of the mechanism moves in a circle with a large nutation angle, the comprehensive influence coefficient of each sensitivity is the largest. Residual analysis shows that the robustness of the identification algorithm with the idea of PCA is improved. Through experiments, it is found that the compensation effect is improved.

A model for optimizing the position and attitude trajectory of error measurement is proposed, which can effectively improve the error measurement efficiency of the 1T2R parallel mechanism. In addition, the PCA idea is introduced. A least-squares PCA error identification algorithm that improves the robustness of the identification algorithm by improving the property of the identification matrix is proposed, and the compensation effect is improved. This method has been verified by experiments on 1T2R parallel mechanism and can be extended to other similar parallel mechanisms.

The purpose of this paper is to describe a novel error‐ranking methodology and two compensation strategies for hybrid parallel kinematic machines (HPKMs).

The paper outlines an error analysis methodology developed for HPKMs and applies the technique to a typical industrial HPKM. Based on the results of this, two compensation strategies are developed and implemented, for both mass‐induced and thermal errors.

The paper demonstrates and quantifies the performance improvements possible with appropriate error compensation strategies.

The paper introduces a novel and generic methodology for error source analysis and describes two fully implemented compensation strategies which result in a significantly improved level of system performance.

The purpose of this paper is to improve the accuracy of fused deposition modeling (FDM) machines.

An integrated error model and compensation methods are developed to improve the accuracy of FDM machines. The effects of machine-dependent and process-dependent errors are included in this integrated model. The error model is then used to obtain compensated values for the printed object. A three-dimensional artifact is designed for the FDM machine characterization. This process takes place only once and an error model for the machine is then developed. An artifact is designed that is feature rich and its coordinates are measured by the coordinate measuring machine (CMM). The CMM digitized values for the three-dimensional artifact are used to calculate the coefficients of the model. The integrated error model of the machine can be used to obtain the compensated values for any given part models. The coefficients of the integrated error model are machine-dependent and represent machine error estimation. To demonstrate this, two test examples are used and modified based on the machine model to verify the effectiveness of the proposed method.

The errors from machine mechanical structure and process are evaluated. The variation trend of each error is analyzed. The uncompensated and compensated models are compared, and the effectiveness of the integrated error model and compensation method is analyzed and validated.

An effective integrated error model with compensation is developed, which can be used to improve the FDM machines accuracy.

This study aims to improve the positioning accuracy of a large-scale parallel pose alignment mechanism by calibration and error compensation.

The dynamic modelling of the parallel pose alignment mechanism is achieved using the Newton Euler method. Combined with a deformation compatibility analysis, the support force at the spherical hinge and the friction of the follow-up prismatic pair are calculated. The deformation of the moving platform in multi-pose space is analysed by the integral method, and a corresponding deformation model is established. Based on the calculated support force, friction and deformation, the deformation error is analysed. Combined with the calculated deformation error, kinematics calibration and positioning error compensation are carried out.

The simulation results show that the deviation of structural error identification is decreased from 3.03 × 10^–1 mm to 6.8 × 10^–2 mm. The experimental results show that the maximum pose errors after compensation are reduced from 2.77 mm to 6.5 × 10^–1° to 3.9 × 10^–1 mm and 3.7 × 10^–1°, which verifies the effectiveness of the proposed method.

This method can be used in the field of aircraft assembly for the calibration and error compensation of a large-scale parallel pose alignment mechanism based on positioners.

Large size of aircraft assembly tooling structure and complex measurement environment exist. The laid enhanced reference points (ERS) are subject to a combination of nonuniform temperature fields and measurement errors, resulting in increased measurement registration errors. In view of the nonuniform temperature field and measurement errors affecting the ERS point registration problem, the purpose of this paper is to propose a neural network-based ERS point registration compensation method for large-size measurement fields under a nonuniform temperature field.

The approach is to collect ERS point information and temperature data, normalize the collected data to complete the data structure design and complete the construction of the neural network prediction model by data training. The data learning is performed to complete the prediction model construction, and the prediction model is used to complete the compensation analysis of ERS points. Finally, the algorithm is verified through experiments and engineering practice.

Experimental results show that the proposed neural network-based ERS point prediction and compensation method for nonuniform temperature fields effectively predicts ERS point deformation under nonuniform temperature fields compared with the conventional method. After the compensation analysis, the registration error is effectively reduced to improve registration accuracy. Reducing the combined effect of environmental nonuniform temperature field and measurement error has apparent advantages.

The method reduces the registration error caused by combining a nonuniform temperature field and measurement error. It can be used for aircraft assembly site prediction and registration error compensation analysis, which is essential to improve measurement accuracy further.

The lack of geometric and dimensional accuracy of parts produced by additive manufacturing (AM) is directly related to the machine, material and process used. This paper aims to propose a method for the analysis and compensation of machine-related geometric errors applicable to any AM machine, regardless of the manufacturing process and technology used.

For this purpose, an error calculation model inspired by those used in computerized numerical control machines and coordinate measuring machines was developed. The error functions of the model were determined from the position deviations of a set of virtual points that are not sensitive to material and process errors. These points were obtained from the measurement of an ad hoc designed and manufactured master artefact. To validate the model, off-line compensation was applied to both the original designed artefact and an example part.

The geometric deviations in both cases were significantly smaller than those found before applying the geometric compensation. Dimensional enhancements were also achieved on the example part by using a correction parameter available in the three-dimensional printing software, whose value was adjusted from the measurement of the geometrically compensated master artefact.

The errors that persist in the part derive from both material and process. Compensation for these type of errors requires a detailed analysis of the influencing parameters, which will be the subject of future research.

The use of the virtual-point-based error model increases the quality of additively manufactured parts and can be used in any AM system.