THE CALCULATION OF KINEMATIC PARAMETERS OF THE GRIPPER OF THE ТУР-10 INDUSTRIAL ROBOT

2013 ◽  
pp. 47-57
Author(s):  
Anatoliy Vasilyevich Loktionov ◽  
Alexey Petrovich Prokhorov
Keyword(s):  
Industrial Robot ◽  
Kinematic Parameters

A simple and rapid calibration methodology for industrial robot based on geometric constraint and two-step error

2018 ◽  
Vol 45 (6) ◽  
pp. 715-721 ◽  
Author(s):  
Jiabo Zhang ◽  
Xibin Wang ◽  
Ke Wen ◽  
Yinghao Zhou ◽  
Yi Yue ◽  
...  
Keyword(s):  
Coordinate System ◽  
Large Scale ◽  
Industrial Robot ◽  
Geometric Constraint ◽  
Machining Process ◽  
Kinematic Parameters ◽  
Robot Calibration ◽  
Positioning Accuracy ◽  
Content Type ◽  
Rapid Calibration

Purpose The purpose of this study is the presentation and research of a simple and rapid calibration methodology for industrial robot. Extensive research efforts were devoted to meet the requirements of online compensation, closed-loop feedback control and high-precision machining during the flexible machining process of robot for large-scale cabin. Design/methodology/approach A simple and rapid method to design and construct the transformation relation between the base coordinate system of robot and the measurement coordinate system was proposed based on geometric constraint. By establishing the Denavit–Hartenberg model for robot calibration, a method of two-step error for kinematic parameters calibration was put forward, which aided in achievement of step-by-step calibration of angle and distance errors. Furthermore, KUKA robot was considered as the research object, and related experiments were performed based on laser tracker. Findings The experimental results demonstrated that the accuracy of the coordinate transformation could reach 0.128 mm, which meets the transformation requirements. Compared to other methods used in this study, the calibration method of two-step error could significantly improve the positioning accuracy of robot up to 0.271 mm. Originality/value The methodology based on geometric constraint and two-step error is simple and can rapidly calibrate the kinematic parameters of robot. It also leads to the improvement in the positioning accuracy of robot.

Industrial Robot Kinematics Parameter Identification

2014 ◽  
Vol 889-890 ◽  
pp. 1136-1143
Author(s):  
Yong Gui Zhang ◽  
Chen Rong Liu ◽  
Peng Liu
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Parameter Identification ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Robot Kinematics ◽  
Kinematic Parameters ◽  
Unknown Parameters ◽  
Preliminary Measurement ◽  
Kinematics Modeling

For an industrial robots with unknown parameters, on the basis of preliminary measurement and data of the Cartesian and joints coordinates which are shown on the FlexPendant, the kinematic parameters is identified by using genetic algorithms and accurate kinematics modeling of the robot is established. Experimental data could prove the validity of this method.

The Trajectory Planning and Simulation for Industrial Robot Based on Fifth-Order B-Splines

2014 ◽  
Vol 538 ◽  
pp. 367-370 ◽  
Author(s):  
Zhi Jian Gou ◽  
Cheng Wang
Keyword(s):  
Trajectory Planning ◽  
Industrial Robot ◽  
Joint Space ◽  
Robot Kinematics ◽  
Kinematic Parameters ◽  
B Spline ◽  
B Splines ◽  
Robot Trajectory ◽  
Fifth Order ◽  
Parameter Constraints

The trajectory is planned with fifth-order uniform B-splines for the industrial robot aimed to assure the motion is smooth and the trajectory is fourth-order continuous. Under the premise to satisfy the initial kinematic parameters of the robot as zero, its speed, acceleration and jerk are continuous. Based on B-spline theory, process five B-spline curve function is calculated inversely in joint space. Under the robot kinematics parameter constraints, using fifth-order B-spline interpolates to plan robot trajectory when known interpolation points and the kinematic parameters are simulated and validated by the software of ADAMS.So it provides an effective new method for the trajectory planning.

scholarly journals Vibration Suppression for Improving the Estimation of Kinematic Parameters on Industrial Robots

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
David Alejandro Elvira-Ortiz ◽  
Rene de Jesus Romero-Troncoso ◽  
Arturo Yosimar Jaen-Cuellar ◽  
Luis Morales-Velazquez ◽  
Roque Alfredo Osornio-Rios
Keyword(s):  
Kalman Filter ◽  
Sensor Fusion ◽  
Vibration Suppression ◽  
Industrial Robot ◽  
Angular Position ◽  
Industrial Robots ◽  
Industrial System ◽  
Kinematic Parameters ◽  
Fusion Technique ◽  
Motion Profile

Vibration is a phenomenon that is present on every industrial system such as CNC machines and industrial robots. Moreover, sensors used to estimate angular position of a joint in an industrial robot are severely affected by vibrations and lead to wrong estimations. This paper proposes a methodology for improving the estimation of kinematic parameters on industrial robots through a proper suppression of the vibration components present on signals acquired from two primary sensors: accelerometer and gyroscope. A Kalman filter is responsible for the filtering of spurious vibration. Additionally, a sensor fusion technique is used to merge information from both sensors and improve the results obtained using each sensor separately. The methodology is implemented in a proprietary hardware signal processor and tested in an ABB IRB 140 industrial robot, first by analyzing the motion profile of only one joint and then by estimating the path tracking of two welding tasks: one rectangular and another one circular. Results from this work prove that the sensor fusion technique accompanied by proper suppression of vibrations delivers better estimation than other proposed techniques.

scholarly journals Kinematic Calibration of Industrial Robots Based on Distance Information Using a Hybrid Identification Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guanbin Gao ◽  
Yuan Li ◽  
Fei Liu ◽  
Shichang Han
Keyword(s):  
Industrial Robot ◽  
Kinematic Model ◽  
Error Model ◽  
Industrial Robots ◽  
Kinematic Calibration ◽  
Kinematic Parameters ◽  
Distance Information ◽  
End Effector ◽  
Hybrid Identification ◽  
Identification Method

To improve the positioning accuracy of industrial robots and avoid using the coordinates of the end effector, a novel kinematic calibration method based on the distance information is proposed. The kinematic model of an industrial robot is established. The relationship between the moving distance of the end effector and the kinematic parameters is analyzed. Based on the results of the analysis and the kinematic model of the robot, the error model with displacements as the reference is built, which is linearized for the convenience of the following identification. The singular value decomposition (SVD) is used to eliminate the redundant parameters of the error model. To solve the problem that traditional optimization algorithms are easily affected by data noise in high dimension identification, a novel extended Kalman filter (EKF) and regularized particle filter (RPF) hybrid identification method is presented. EKF is used in the preidentification of the linearized error model. With the preidentification results as the initial parameters, RPF is used to identify the kinematic parameters of the linearized error model. Simulations are carried out to validate the effectiveness of the proposed method, which shows that the method can identify the error of the parameters and after compensation the accuracy of the robot is improved.

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