Path tracking control method of transfer robot based on neural network

A handling robot, path tracking technology, applied in neural learning methods, biological neural network models, two-dimensional position/channel control, etc., can solve problems such as poor real-time performance of nonlinear model predictive control

Active Publication Date: 2020-09-04
UNIV OF SCI & TECH BEIJING
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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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  • Path tracking control method of transfer robot based on neural network
  • Path tracking control method of transfer robot based on neural network
  • Path tracking control method of transfer robot based on neural network

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Embodiment Construction

[0069] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0070] Aiming at the problem of poor real-time performance of existing nonlinear model predictive control, the present invention provides a path tracking control method for a handling robot based on a neural network.

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

[0072] S101, using nonlinear model predictive control to generate a training sample set, wherein the training samples include: state variables and control variables of the handling robot;

[0073] S102, constructing a neural network model;

[0074] S103, using the obtained training sample set to train the constructed neural network model to obtain a trained neural ne...

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Abstract

The invention provides a path tracking control method of a transfer robot based on a neural network. The method can improve the real-time performance of nonlinear model prediction control. The methodcomprises the steps: generating a training sample set through nonlinear model predictive control, wherein the training samples comprise state variables and control variables of the transfer robot; constructing a neural network model; and training the constructed neural network model by using the obtained training sample set to obtain a trained neural network model, wherein in the path tracking control process, the trained neural network model outputs a control variable, so that the transfer robot performs path tracking according to the control variable output by the neural network model. The invention relates to the field of mobile robot autonomous driving control.

Description

technical field [0001] The invention relates to the field of autonomous driving control of a mobile robot, in particular to a path tracking control method for a handling robot based on a neural network. Background technique [0002] The unmanned autonomous navigation of the handling robot is to collect the real-time position and pose information of the vehicle through the installed environment collection equipment, such as the Global Positioning System (Global Positioning System, GPS), Ultra Wide Band (Ultra Wide Band, UWB) and other equipment, and then The collected information is input to the path planning module, and then an optimal path is planned, which is passed to the path tracking control module, and the optimal control amount is calculated and sent to the executive agency to complete the automatic driving. The handling robot can track from its location along a planned feasible path and quickly reach the designated place, which is the path tracking problem of the han...

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Application Information

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Patent Type & Authority Applications(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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