Absolute accuracy analysis and improvement of a hybrid 6-DOF medical robot

2015 ◽  
Vol 42 (1) ◽  
pp. 44-53 ◽  
Author(s):  
Ahmed Joubair ◽  
Long Fei Zhao ◽  
Pascal Bigras ◽  
Ilian Bonev
Keyword(s):  
Measurement Errors ◽  
Degrees Of Freedom ◽  
Experimental Tests ◽  
Maximum Error ◽  
Calibration Method ◽  
Calibration Model ◽  
Medical Robot ◽  
Content Type ◽  
Observability Index ◽  
Forward Kinematic

Purpose – The purpose of this paper is to describe a calibration method developed to improve the accuracy of a six degrees-of-freedom medical robot. The proposed calibration approach aims to enhance the robot’s accuracy in a specific target workspace. A comparison of five observability indices is also done to choose the most appropriate calibration robot configurations. Design/methodology/approach – The calibration method is based on the forward kinematic approach, which uses a nonlinear optimization model. The used experimental data are 84 end-effector positions, which are measured using a laser tracker. The calibration configurations are chosen through an observability analysis, while the validation after calibration is carried out in 336 positions within the target workspace. Findings – Simulations allowed finding the most appropriate observability index for choosing the optimal calibration configurations. They also showed the ability of our calibration model to identify most of the considered robot’s parameters, despite measurement errors. Experimental tests confirmed the simulation findings and showed that the robot’s mean position error is reduced from 3.992 mm before calibration to 0.387 mm after, and the maximum error is reduced from 5.957 to 0.851 mm. Originality/value – This paper presents a calibration method which makes it possible to accurately identify the kinematic errors for a novel medical robot. In addition, this paper presents a comparison between the five observability indices proposed in the literature. The proposed method might be applied to any industrial or medical robot similar to the robot studied in this paper.

Obstacle detection based on depth fusion of lidar and radar in challenging conditions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guotao Xie ◽  
Jing Zhang ◽  
Junfeng Tang ◽  
Hongfei Zhao ◽  
Ning Sun ◽  
...  
Keyword(s):  
False Alarm ◽  
Experimental Tests ◽  
Point Clouds ◽  
Calibration Method ◽  
Obstacle Detection ◽  
Environmental Perception ◽  
Fusion Model ◽  
Content Type ◽  
Self Calibration ◽  
Temporal Relationships

Purpose To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection. Design/methodology/approach Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist. Findings The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions. Originality/value A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

An improved vision calibration method for coaxial alignment microassembly

2014 ◽  
Vol 34 (3) ◽  
pp. 237-243 ◽  
Author(s):  
Xin Ye ◽  
Jun Gao ◽  
Zhijing Zhang ◽  
Chao Shao ◽  
Guangyuan Shao
Keyword(s):  
Degrees Of Freedom ◽  
Microelectromechanical Systems ◽  
Vision System ◽  
Image Plane ◽  
Calibration Method ◽  
Corner Detection ◽  
Objective Lens ◽  
Content Type ◽  
Assembly Accuracy ◽  
Methodological Guidelines

Purpose – The purpose of this paper is to propose a sub-pixel calibration method for a microassembly system with coaxial alignment function (MSCA) because traditional sub-pixel calibration approaches cannot be used in this system. Design/methodology/approach – The in-house microassembly system comprises a six degrees of freedom (6-DOF) large motion serial robot with microgrippers, a hexapod 6-DOF precision alignment worktable and a vision system whose optical axis of the microscope is parallel with the horizontal plane. A prism with special coating is fixed in front of the objective lens; thus, two parts’ Figures, namely the images of target and base part, can be acquired simultaneously. The relative discrepancy between the two parts can be calculated from image plane coordinate instead of calculating space transformation matrix. Therefore, the traditional calibration method cannot be applied in this microassembly system. An improved calibration method including the check corner detection solves the distortion coefficient conversely. This new way can detect the corner at sub-pixel accuracy. The experiment proves that the assembly accuracy of the coaxial microassembly system which has been calibrated by the new method can reach micrometer level. Findings – The calibration results indicate that solving the distortion conversely could improve the assembly accuracy of MSCA. Originality/value – The paper provides certain calibration methodological guidelines for devices with 2 dimensions or 2.5 dimensions, such as microelectromechanical systems devices, using MSCA.

A distance error based industrial robot kinematic calibration method

2014 ◽  
Vol 41 (5) ◽  
pp. 439-446 ◽  
Author(s):  
Wang Zhenhua ◽  
Xu Hui ◽  
Chen Guodong ◽  
Sun Rongchuan ◽  
Lining Sun
Keyword(s):  
Industrial Robot ◽  
Calibration Method ◽  
Calibration Model ◽  
Kinematic Calibration ◽  
Absolute Position ◽  
Positioning Accuracy ◽  
Content Type ◽  
Distance Error ◽  
Position Accuracy ◽  
The Absolute

Purpose – The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate. Design/methodology/approach – In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section. Findings – The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically. Originality/value – The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

A calibration method of kinematic parameters for serial industrial robots

2014 ◽  
Vol 41 (2) ◽  
pp. 157-165 ◽  
Author(s):  
Wei Wang ◽  
Gang Wang ◽  
Chao Yun
Keyword(s):  
Calibration Method ◽  
Error Model ◽  
Industrial Robots ◽  
Reference Configuration ◽  
Calibration Model ◽  
Positioning Error ◽  
Kinematic Parameters ◽  
Rigid Displacement ◽  
Content Type ◽  
Zero Position

Purpose – Calibrating kinematic parameters is one of the efficient ways to improve the robot's positioning accuracy. A method based on the product-of-exponential (POE) formula to calibrate the kinematic parameters of serial industrial robots is proposed. The paper aims to discuss these issues. Design/methodology/approach – The forward kinematics is established, and the general positioning error model is deduced in an explicit expression. A simplified model of robot's positioning error is established as both the error of reference configuration and the error of rigid displacement of the base coordinating system with respect to the measuring coordinating system are equivalently transferred to the zero position errors of the robot's joints. A practical calibration model is forwarded only requiring 3D measuring based on least-squares algorithm. The calibration system and strategy for calibrating kinematic parameters are designed. Findings – By the two geometrical constrains between the twist coordinates, each joint twist only has four independent coordinates. Due to the equivalent error model, the zero position error of each joint can cover the error of reference configuration and rigid displacement of the robot base coordinating system with respect to the measuring coordinating system. The appropriate number of independent kinematic parameters of each joint to be calibrated is five. Originality/value – It is proved by a group of calibration experiments that the calibration method is well conditioned and can be used to promote the level of absolute error of end effector of industrial robot to 2.2 mm.

scholarly journals Two-Step Calibration Method for Inverse Finite Element with Small Sample Features

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4602
Author(s):  
Libo Xu ◽  
Feifei Zhao ◽  
Jingli Du ◽  
Hong Bao
Keyword(s):  
Finite Element ◽  
Measurement Errors ◽  
Degrees Of Freedom ◽  
Calibration Method ◽  
Small Sample ◽  
Deformation Field ◽  
Reconstruction Accuracy ◽  
Fem Method ◽  
Measured Strain ◽  
Fuzzy Network

When the inverse finite element method (inverse FEM) is used to reconstruct the deformation field of a multi-element structure with strain measurements, strain measurement errors can lower the reconstruction accuracy of the deformation field. Furthermore, the calibration ability of a self-structuring fuzzy network (SSFN) is weak when few strain samples are used to train the SSFN. To solve this problem, a novel two-step calibration method for improving the reconstruction accuracy of the inverse FEM method is proposed in this paper. Initially, the errors derived from measured displacements and reconstructed displacements are distributed to the degrees of freedom (DOFs) of nodes. Then, the DOFs of nodes are used as knots, in order to produce non-uniform rational B-spline (NURBS) curves, such that the sample size employed to train the SSFN can be enriched. Next, the SSFN model is used to determine the relationship between the measured strain and the DOFs of the end nodes. A loading deformation experiment using a three-element structure demonstrates that the proposed algorithm can significantly improve the accuracy of reconstruction displacement.

Using a Maximum Error Statistic to Evaluate Measurement Errors in 3D Position and Orientation Tracking Systems

1993 ◽  
Vol 2 (4) ◽  
pp. 314-343 ◽  
Author(s):  
Ted Morris ◽  
Max Donath
Keyword(s):  
Relative Motion ◽  
Measurement Errors ◽  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Computer Experiments ◽  
Maximum Error ◽  
Tracking Systems ◽  
3D Motion ◽  
Six Degrees Of Freedom ◽  
Error Statistic

One approach to tracking anatomical and robot joint motion consists of tracking the XYZ locations of multiple point targets that are attached to each of the moving segments and then computing the three translations and three orientation angles between adjoining segments. The complexity of such systems requires that we introduce a new conservative maximum error statistic to be used for evaluating the accuracy of 3D motion tracking systems. This paper addresses the various phenomena that contribute to measurement error when computing six degrees of freedom associated with the relative motion between the adjacent segments. The characteristics of these errors, common to many 3D motion tracking systems, were first determined by experimentation using one such system (MnSCAN). These and additional artifacts were then modeled in order to quantitatively evaluate their effects using the maximum error statistic. Based on these computer experiments, several relationships were identified that predict how each of these phenomena influences the predicted measurement of relative motion between bodies. These suggest where design emphasis should be placed in order to minimize the error in tracking the six degrees of freedom. The methodology and the conclusions based on these results can be applied to designing most six degree of freedom position and motion measurement systems.

On-line self-calibration method for unattended manipulators based on Gaussian motion model and visual system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruolong Qi ◽  
Yuangui Tang ◽  
Ke Zhang
Keyword(s):  
Visual System ◽  
High Precision ◽  
Measurement Errors ◽  
Structural Parameters ◽  
Space Station ◽  
Calibration Method ◽  
Nuclear Industry ◽  
Industrial Robots ◽  
Content Type ◽  
On Line

Purpose For some special manipulators such as the ones work at the space station, nuclear or some other unmanned environments, the overload, collision, vibration, temperature change or release of the internal stress would affect the structural parameters. And thus the operation precision might constantly decrease in long-term use. In these unmanned environments, the unattended manipulators should calibrate itself when they execute high precision operations or proceed self-maintenances. The purpose of this paper is to propose an automatic visual assistant on-line calibration (AVOC) method based on multi-markers. Design/methodology/approach A camera fixed on the end of the manipulator is used to measure one to three identification points, which forms an unstable multi-sensor eye-in-hand system. A Gaussian motion method which combines the linear quadratic regulator control and extended Kalman filter together is proposed to make the manipulator track the planned trajectories when its inaccurate structural parameters form uncertain motion errors. And a Monte-Carlo method is proposed to form a high precision and stable signal acquisition when the visual system has measurement errors and intermittent signal feedback. An automatic sampling process is adopted to select the optimal measurement points basing on their variances. Findings Data analysis and experiment results prove the efficiency and feasibility of the method proposed in this paper. With this method, the positioning accuracy is largely promoted from about 2 mm to 0.04–0.05 mm. Originality/value Experiments were carried out successfully on a manipulator in a life sciences glove box that will work at the Chinese space station. It is a low cost and efficient manipulator calibration method. The whole autonomic calibration process takes less than 10 min and requires no human intervention. In addition, this method not only can be used in the calibration of other unmanned articulated manipulator that works in deep ocean, nuclear industry or space but also be useful for the maintenance work in modern factories owing a lot of industrial robots.

A self-calibration method for rotary tables’ five degrees-of-freedom error motions

Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109067
Author(s):  
Zhi-Feng Lou ◽  
Li Liu ◽  
Ji-Yun Zhang ◽  
Kuang-chao Fan ◽  
Xiao-Dong Wang
Keyword(s):  
Degrees Of Freedom ◽  
Calibration Method ◽  
Self Calibration

scholarly journals Torque Ripple Suppression of PMSM Based on Robust Two Degrees-of-Freedom Resonant Controller

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1015
Author(s):  
Mingfei Huang ◽  
Yongting Deng ◽  
Hongwen Li ◽  
Jing Liu ◽  
Meng Shao ◽  
...  
Keyword(s):  
Control Strategy ◽  
Measurement Errors ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Torque Ripple ◽  
Current Loop ◽  
Two Degrees Of Freedom ◽  
Robust Stability Analysis ◽  
Resonant Controller ◽  
Testing Environments

This paper concentrates on a robust resonant control strategy of a permanent magnet synchronous motor (PMSM) for electric drivers with model uncertainties and external disturbances to improve the control performance of the current loop. Firstly, to reduce the torque ripple of PMSM, the resonant controller with fractional order (FO) calculus is introduced. Then, a robust two degrees-of-freedom (Robust-TDOF) control strategy was designed based on the modified resonant controller. Finally, by combining the two control methods, this study proposes an enhanced Robust-TDOF regulation method, named as the robust two degrees-of-freedom resonant controller (Robust-TDOFR), to guarantee the robustness of model uncertainty and to further improve the performance with minimized periodic torque ripples. Meanwhile, a tuning method was constructed followed by stability and robust stability analysis. Furthermore, the proposed Robust-TDOFR control method was applied in the current loop of a PMSM to suppress the periodic current harmonics caused by non-ideal factors of inverter and current measurement errors. Finally, simulations and experiments were performed to validate our control strategy. The simulation and experimental results showed that the THDs (total harmonic distortion) of phase current decreased to a level of 0.69% and 5.79% in the two testing environments.

scholarly journals A New Approach of Soft Joint Based on a Cable-Driven Parallel Mechanism for Robotic Applications

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1468
Author(s):  
Luis Nagua ◽  
Carlos Relaño ◽  
Concepción A. Monje ◽  
Carlos Balaguer
Keyword(s):  
Parallel Mechanism ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Experimental Tests ◽  
Humanoid Robots ◽  
Inverse Kinematic ◽  
Element Analysis ◽  
New Approach ◽  
Flexible Polymer ◽  
The Mathematical Model

A soft joint has been designed and modeled to perform as a robotic joint with 2 Degrees of Freedom (DOF) (inclination and orientation). The joint actuation is based on a Cable-Driven Parallel Mechanism (CDPM). To study its performance in more detail, a test platform has been developed using components that can be manufactured in a 3D printer using a flexible polymer. The mathematical model of the kinematics of the soft joint is developed, which includes a blocking mechanism and the morphology workspace. The model is validated using Finite Element Analysis (FEA) (CAD software). Experimental tests are performed to validate the inverse kinematic model and to show the potential use of the prototype in robotic platforms such as manipulators and humanoid robots.

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