scholarly journals A Graph Theory-Based Method for Dynamic Modeling and Parameter Identification of 6-DOF Industrial Robots

2021 ◽  
Vol 11 (22) ◽  
pp. 10988
Author(s):  
Jun Cheng ◽  
Shusheng Bi ◽  
Chang Yuan ◽  
Lin Chen ◽  
Yueri Cai ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Dynamic Model ◽  
Dynamic Modeling ◽  
Theoretical Basis ◽  
Dynamic Parameter ◽  
Dynamic Parameters ◽  
Precision Manufacturing ◽  
Robot System ◽  
Precise Control ◽  
Dynamic Parameter Identification

At present, the absolute positioning accuracy and control accuracy of industrial serial robots need to be improved to meet the accuracy requirements of precision manufacturing and precise control. An accurate dynamic model is an important theoretical basis for solving this problem, and precise dynamic parameters are the prerequisite for precise control. The research of dynamics and parameter identification can greatly promote the application of robots in the field of precision manufacturing and automation. In this paper, we study the dynamical modeling and dynamic parameter identification of an industrial robot system with six rotational DOF (6R robot system) and propose a new method for identifying dynamic parameters. Our aim is to provide an accurate mathematical description of the dynamics of the 6R robot and to accurately identify its dynamic parameters. First, we establish an unconstrained dynamic model for the 6R robot system and rewrite it to obtain the dynamic parameter identification model. Second, we establish the constraint equations of the 6R robot system. Finally, we establish the dynamic model of the constrained 6R robot system. Through the ADAMS simulation experiment, we verify the correctness and accuracy of the dynamic model. The experiments prove that the result of parameter identification has extremely high accuracy and the dynamic model can accurately describe the 6R robot system mathematically. The dynamic modeling method proposed in this paper can be used as the theoretical basis for the study of 6R robot system dynamics and the study of dynamics-based control theory.

Dynamic Parameter Identification of Unknown Object Handled by Space Manipulator

2014 ◽  
Vol 487 ◽  
pp. 276-281 ◽  
Author(s):  
Gang Chen ◽  
Zhi Lian Chen ◽  
Qing Xuan Jia ◽  
Han Xu Sun
Keyword(s):  
Parameter Identification ◽  
Dynamic Characteristic ◽  
Dynamic Parameter ◽  
Momentum Conservation ◽  
Dynamic Parameters ◽  
Robot System ◽  
Space Manipulator ◽  
Experimental Process ◽  
Dynamic Parameter Identification ◽  
Unknown Object

This paper presents a dynamic parameter identification method of the unknown object handled by manipulator. Since the load will change the dynamic characteristic of space robot system, it is necessary to identify the dynamic parameters of the handled object. The dynamic parameters of the handled object are identified based on principle of momentum conservation in this paper. The principle and experimental process of the identification is introduced and the feasibility of the method is verified by simulation.

Dynamic Parameter Identification of the Base of a Space Robot when Considering the Gravity Gradient

2014 ◽  
Vol 945-949 ◽  
pp. 1384-1389 ◽  
Author(s):  
Han Xu Sun ◽  
Zhi Lian Chen ◽  
Gang Chen ◽  
Qing Xuan Jia
Keyword(s):  
Parameter Identification ◽  
Significant Role ◽  
Dynamic Parameter ◽  
Momentum Conservation ◽  
Space Robot ◽  
Gravity Gradient ◽  
Dynamic Parameters ◽  
Robot System ◽  
Experimental Process ◽  
Dynamic Parameter Identification

This paper presents a dynamic parameter identification method of the base of a free-flying space robot. Since the dynamic parameters play a significant role in the control of space robot system, it is necessary to identify the dynamic parameters of a space robot. First the dynamic parameters of the base are identified based on principle of momentum conservation in this paper. Then gravity gradient torque is used to identify the product of inertia for that it has effect on the attitude of a space robot. The principle and experimental process of the identification are introduced and the feasibility of the method is verified by simulation.

scholarly journals A dynamic parameter identification method of industrial robots considering joint elasticity

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141882521 ◽  
Author(s):  
Hepeng Ni ◽  
Chengrui Zhang ◽  
Tianliang Hu ◽  
Teng Wang ◽  
Qizhi Chen ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Dynamic Model ◽  
Joint Stiffness ◽  
Dynamic Parameter ◽  
Industrial Robots ◽  
Identification Accuracy ◽  
Processing Algorithm ◽  
Identification Method ◽  
Joint Elasticity ◽  
Dynamic Parameter Identification

Considering the joint elasticity, a novel dynamic parameter identification method is proposed for general industrial robots only with motor encoders. Firstly, the unknown parameters of the elastic joint dynamic model are analyzed and divided into two types. The first type is the motion-independent parameter only including the joint stiffness, which can be identified by the static force/torque-deformation experiments without the dynamic model. The second type is the motion-dependent parameter composed of the rest of the parameters, which needs the dynamic excitation experiments. Therefore, these two types of parameters can be identified separately. Meanwhile, it is found that the rotor inertia parameters can be obtained from the manufacturer, which reduces the identification difficulty of other parameters. After obtaining the rotor inertia and joint stiffness, an approximate processing algorithm is proposed considering the motor friction to establish the linear identification model of other parameters. Hence, the least squares can be employed to identify the parameters, and the independence of the inertia and joint viscous friction parameters are not affected. Meanwhile, the exciting trajectories can be optimized throughout the robot workspace, which reduces the effect of measurement noise on identification accuracy. With the proposed separated identification strategy and approximate processing algorithm, the dynamic parameters can be obtained precisely without double encoders on each joint. Finally, a series of simulations are conducted to evaluate the good performance of the proposed method.

Identification of Dynamic Parameter of a 3DOF Parallel Manipulator With Actuation Redundancy

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Jun Wu ◽  
Jinsong Wang ◽  
Liping Wang
Keyword(s):  
Parameter Identification ◽  
Dynamic Equation ◽  
Parallel Manipulator ◽  
Virtual Work ◽  
Dynamic Parameter ◽  
Rigid Body Dynamics ◽  
Dynamic Parameters ◽  
Actuation Redundancy ◽  
Point To Point ◽  
Dynamic Parameter Identification

This paper deals with the dynamic parameter identification of a 3DOF parallel manipulator with actuation redundancy. A method for finding the parameter linear form of the dynamic equation is presented. Based on the virtual work principle, the dynamic equation for the application of dynamic parameter identification is obtained by extracting the dynamic parameters from inertial forces and moments of moving parts. Two-step identification approach is used to identify the dynamic parameters of the redundantly actuated parallel manipulator. The approach consists of two steps and utilizes simple point-to-point motions that lead to a separation of friction and rigid-body dynamics. The identified results are validated by experiments. Moreover, the experimental application of the identified model to a machine tool, which is created by combining the parallel manipulator with a 2DOF worktable, demonstrates the efficiency of dynamic parameter identification.

A novel approach for experimental identification of vehicle dynamic parameters

2020 ◽  
Vol 234 (10-11) ◽  
pp. 2634-2648
Author(s):  
Di Yao ◽  
Philipp Ulbricht ◽  
Stefan Tonutti ◽  
Kay Büttner ◽  
Prokop Günther
Keyword(s):  
Parameter Identification ◽  
Dynamic Modeling ◽  
Trajectory Optimization ◽  
Dynamic Parameters ◽  
Vehicle Dynamic ◽  
Test Rig ◽  
Vehicle Simulation ◽  
Virtual Test ◽  
Identification Approach ◽  
Measuring Machine

Pervasive applications of the vehicle simulation technology are a powerful motivation for the development of modern automobile industry. As basic parameters of road vehicle, vehicle dynamic parameters can significantly influence the ride comfort and dynamics of vehicle, and therefore have to be calculated accurately to obtain reliable vehicle simulation results. Aiming to develop a general solution, which is applicable to diverse test rigs with different mechanisms, a novel model-based parameter identification approach using optimized excitation trajectory is proposed in this paper to identify the vehicle dynamic parameters precisely and efficiently. The proposed approach is first verified against a virtual test rig using a universal mechanism. The simulation verification consists of four sections: (a) kinematic analysis, including the analysis of forward/inverse kinematic and singularity architecture; (b) dynamic modeling, in which three kinds of dynamic modeling method are used to derive the dynamic models for parameter identification; (c) trajectory optimization, which aims to search for the optimal trajectory to minimize the sensitivity of parameter identification to measurement noise; and (d) multibody simulation, by which vehicle dynamic parameters are identified based on the virtual test rig in the simulation environment. In addition to the simulation verification, the proposed parameter identification approach is applied to the real test rig (vehicle inertia measuring machine) in laboratory subsequently. Despite the mechanism difference between the virtual test rig and vehicle inertia measuring machine, this approach has shown an excellent portability. The experimental results indicate that the proposed parameter identification approach can effectively identify the vehicle dynamic parameters without a high requirement of movement accuracy.

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