Assembly control method based on long short-term memory neural network incremental model

A technology of long-term short-term memory and neural network, which is applied in the field of assembly control based on the incremental model of long-term short-term memory neural network. It can solve the problems of large motion delay, low control precision, and low precision, so as to reduce errors and improve accuracy. , high precision effect

Inactive Publication Date: 2019-08-23
TSINGHUA UNIV
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Problems solved by technology

[0005] The purpose of the invention is to overcome the large motion time delay and low accuracy of the existing white-box model based on dynamics principle online simulation control virtual model and physical entity and the black-box model based

Method used

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Embodiment Construction

[0031] The present invention proposes a kind of assembly control method based on long-short-term memory neural network incremental model, further detailed description below in conjunction with specific embodiment as follows.

[0032] The present invention proposes an assembly control method based on the long-short-term memory neural network incremental model. The method uses modeling software to establish a virtual model for the assembly robot and the assembly task entity of the product to be assembled on the assembly line, and based on the principle of dynamics for the assembly robot. Precise control of motion pose, planning a feasible assembly plan through virtual assembly, and then realizing real-time accurate mapping between virtual and real models through this method, so that the actual assembly can meet the error requirements of virtual assembly, so as to maintain the virtual model and equipment entities in the same position. Spatiotemporal consistency during motion.

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Abstract

The invention provides a control method based on a long short-term memory neural network incremental model, and belongs to the technical field of intelligent control of information physical systems. According to the method, virtual models are established for a to-be-assembled product, an assembly robot and an assembly task entity which are on an assembly line through modeling software, and the movement pose of the assembly robot is accurately controlled on the basis of the dynamics principle; a feasible assembly scheme is planned through virtual assembly, real-time accurate mapping between thevirtual models and actual models is achieved, the actual assembly meets the error requirements of virtual assembly, so that the spatio-temporal consistency of the virtual models and equipment entityduring the movement process is maintained. According to the control method, the accuracy of a virtual assembly result can be improved, and it is ensured that the actual assembly is successfully completed.

Description

technical field [0001] The invention belongs to the technical field of intelligent control of cyber-physical systems, and in particular proposes an assembly control method based on a long-short-term memory neural network incremental model. Background technique [0002] The six-degree-of-freedom industrial manipulator is a robot that can move and rotate freely in three directions within the manipulator's range of motion and has six degrees of freedom. Because it can complete highly repetitive mechanical work, has a friendly user interface, is easy to operate, supports programming and external drive, and has flexible control, the application of this type of robot in assembly is increasing day by day. The six-degree-of-freedom industrial manipulator on the assembly line can learn its control parameters through agile and diverse sensors, so that the assembly speed is stable, and the positioning is accurate and predictable. [0003] Traditional virtual assembly mainly uses virtu...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1664B25J9/1669
Inventor 张和明刘文正陈佳宁
Owner TSINGHUA UNIV
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