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A Neural Network-Based Path Tracking Control Method for Handling Robot

A handling robot and path tracking technology, applied in neural learning methods, biological neural network models, two-dimensional position/channel control, etc. The effect of high tracking accuracy

Active Publication Date: 2021-07-09
UNIV OF SCI & TECH BEIJING
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a path tracking control method based on a neural network for a handling robot to solve the problem of poor real-time performance of nonlinear model predictive control existing in the prior art

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  • A Neural Network-Based Path Tracking Control Method for Handling Robot
  • A Neural Network-Based Path Tracking Control Method for Handling Robot
  • A Neural Network-Based Path Tracking Control Method for Handling Robot

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Embodiment Construction

[0069] In order to make the technical problems, technical solutions and advantages to solve the present invention more clearly, and will be described in detail below with reference to the accompanying drawings and specific examples.

[0070] The present invention provides a problem of a path tracking control method based on a neural network based on the problem of the conventional nonlinear model predicts the difference in real-time performance.

[0071] Such as figure 1 As shown, the path tracking control method of a neural network-based handling robot is provided in the embodiment of the present invention, including:

[0072] S101, using nonlinear model predictive control generates training sample set, wherein training samples comprise: the status variable and control variables of the robot;

[0073] S102, construct neural network model;

[0074] S103, using the acquired training sample set to train the construction neural network model to obtain a well-trained neural network mo...

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Abstract

The invention provides a path tracking control method of a handling robot based on a neural network, which can improve the real-time performance of nonlinear model predictive control. The method includes: using nonlinear model predictive control to generate a training sample set, wherein the training sample includes: state variables and control variables of the handling robot; constructing a neural network model; using the obtained training sample set to train the constructed neural network model , to obtain a trained neural network model; wherein, in the path tracking control process, the trained neural network model outputs control variables, so that the handling robot performs path tracking according to the control variables output by the neural network model. The invention relates to the field of autonomous driving control of mobile robots.

Description

Technical field [0001] The present invention relates to the field of mobile robots, in particular, refer to a path tracking control method of a neural network based handling robot. Background technique [0002] The unmanned navigation of the handling robot is to collect the vehicle real-time position and position postage information by installed environmental acquisition equipment such as global positioning system (Global Positioning System, GPS), Ultra Wide Band, UWB, and then The acquired information is input to the path planning module, which further plans an optimal path, and transmits the path tracking control module, and calculates the optimal control amount and issues to the actuator to complete the automatic driving. The handling robot can track the operation along a planned feasible path from its location, quickly reaching the designated location, which is the path tracking problem of the handling robot. Path Tracking Control is the most basic and most core function in t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02G06N3/08G06N3/04
CPCG05D1/0212G06N3/084G06N3/045
Inventor 孟宇白国星武俊雪刘丽冯立勇甘鑫
Owner UNIV OF SCI & TECH BEIJING
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