Robot dynamics model identification method

A dynamic model and identification method technology, applied in the field of robot dynamics model, can solve the problems of low identification accuracy and poor consistency of robot dynamics model parameters, and achieve the effect of improving identification accuracy, good consistency and high accuracy

Active Publication Date: 2019-07-30
SHANGHAI JIAO TONG UNIV
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  • Application Information

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Problems solved by technology

[0007] In view of the above-mentioned defects of the prior art, what the present invention aims to solve is the problem of low precision and poor consistency in the identification of robot dynamic model parameters in the prior art

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Embodiment Construction

[0061] The method of the present invention is further described below in conjunction with the accompanying drawings. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following Example.

[0062] The robot of this embodiment is the Foxconn robot whose model is A-05-2, and its six joints are all rotary joints, and the controller used in the embodiment is the MicroLabBox of dSPACE Company, such as figure 1 As shown, this embodiment includes the following steps:

[0063] Step 1, prepare data, collect the torque command of each joint and the feedback position of the joint encoder; let the robot track the excitation curve optimized in advance, record the joint torque command and the feedback position of the encoder at the same time, and then use the Butterfly with zero phase delay ...

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Abstract

The invention discloses a robot dynamics model identification method, and relates to the field of robot dynamics models. The dynamics model identification method comprises three cycles from inside tooutside; the inner-layer cycle is configured to converge a covariance matrix of errors in a dynamics model to a constant value, so that the statistical characteristics of the errors are more accurately calculated; the middle-layer cycle is configured to remove data points not conforming to the model in the data so as to improve the consistency of model parameter estimation; and the outer-layer cycle is configured to update nonlinear friction force model parameters so as to improve the accuracy of model parameter estimation. Compared with a traditional dynamics model identification method, thenovel method is used for analyzing a parameter identification problem from the point of statistics, an iterative weighted least square method is adopted to remove an outlier, a new friction force model is adopted to improve the identification precision, and dynamics model parameters can be identified accurately and robustly in an off-line mode, so that a firm foundation is laid for the design andapplication of a robot.

Description

technical field [0001] The invention relates to the field of robot dynamic models, in particular to a robot dynamic model identification method. Background technique [0002] Dynamic models are widely used in controller design, motion planning with joint force / moment constraints, offline simulation, and design of disturbance observers. Therefore, how to accurately identify the dynamic model is of great significance. [0003] The theoretical basis of robot dynamics model identification matured in the 1980s. The most important theoretical basis is that the robot dynamics model has a linear relationship with its inertial parameters, so that the model parameters can be identified by the least square method. In this regard, Khalil et al. have elaborated in "Modeling, Identification and Control of Robots". [0004] The friction model is particularly important in the process of robot dynamics model identification. On the one hand, the friction force occupies a large proportion i...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16B25J17/02
CPCB25J9/1653B25J17/02
Inventor 吴建华熊振华韩勇史晓立朱向阳
Owner SHANGHAI JIAO TONG UNIV
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