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Humanoid robot walking self-learning control method

A humanoid robot and control method technology, applied in the direction of program control manipulators, manipulators, manufacturing tools, etc., can solve problems such as difficulty in achieving control goals, and achieve the effect of improving control performance

Active Publication Date: 2018-07-03
UNIV OF ELECTRONICS SCI & TECH OF CHINA ZHONGSHAN INST
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, when the robot deviates from the predetermined trajectory, it is sometimes difficult to achieve the expected control goal only through single-joint or double-joint control

Method used

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  • Humanoid robot walking self-learning control method
  • Humanoid robot walking self-learning control method
  • Humanoid robot walking self-learning control method

Examples

Experimental program
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Effect test

Embodiment Construction

[0020] Further illustrate the implementation process of the present invention below in conjunction with accompanying drawing and embodiment

[0021] In this example, the walking quality of the robot is evaluated from three aspects: energy consumption, horizontal and vertical stability, and performance evaluation indicators are designed, which are the horizontal stability margin , vertical stability margin , energy efficiency margin , which is defined as shown in formulas (1)-(3).

[0022] In this example, according to the energy efficiency margin , the horizontal stability margin , vertical stability margin Three performance indicators to evaluate the quality of the sample and design the sample pros and cons coefficient , the better the sample quality, the larger the sample quality coefficient; in particular, the sample quality coefficient The value range of is [0,1].

[0023] According to the above objectives, the following sample pros and cons coefficients can...

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Abstract

The invention discloses a humanoid robot walking self-learning control method. The method is characterized in that performance evaluation indexes can be made from the energy efficiency, the horizontalstability degree and the vertical stability degree respectively through the self-learning control method; the non-linear relationship between all joint angles and zero moment point errors is obtainedby learning walking samples of a robot; the correction quality of all the joint angles is obtained according to the actual zero moment point error, and stable walking is achieved. In order to improvethe learning effect, a sample excellent-inferior coefficient is distributed to each learning sample according to the energy efficiency margin J<ee>, the horizontal stability margin J<zmp> and the vertical stability margin J<yaw> of walking samples, and the control performance is improved according to the principle that the larger the excellent-inferior coefficient is, and the higher the given attention degree is in the learning process. Through the method, the influence of the robot walking sample quality on the control performance is fully considered. The method has the advantages that the application range is wide, and the energy efficiency is high.

Description

technical field [0001] The invention relates to the technical field of humanoid robot control. Specifically, it is a self-learning control method for a humanoid robot. Background technique [0002] Humanoid robot is a nonlinear system with many degrees of freedom, complex structure and strong coupling, among which walking stability is an important basic problem in the field of humanoid robot. According to the walking stability theory of humanoid robot, when the zero-moment point of the robot is in the stable area of ​​the supporting foot, the robot can walk stably. However, due to the influence of uncertain factors such as external force interference and model error, the zero-moment point trajectory of the robot will deviate from the predetermined trajectory during the walking process. If it is not controlled in time, the walking stability will be affected. The control methods of traditional robots are usually based on classical control theory, and stable walking is achiev...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/163
Inventor 杨亮
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA ZHONGSHAN INST
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