Method for realizing self-adaptive walking framework of anthropomorphic robot based on CPG (central pattern generator) model

A technology of a humanoid robot and its implementation method, which is applied in the direction of manipulators, program-controlled manipulators, manufacturing tools, etc., can solve the problems of insufficient stability and adaptability, and achieve the effect of improving adaptability

Active Publication Date: 2018-08-07
CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of insufficient stability and adaptability in the existing CPG-based humanoid robot control

Method used

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  • Method for realizing self-adaptive walking framework of anthropomorphic robot based on CPG (central pattern generator) model
  • Method for realizing self-adaptive walking framework of anthropomorphic robot based on CPG (central pattern generator) model
  • Method for realizing self-adaptive walking framework of anthropomorphic robot based on CPG (central pattern generator) model

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Embodiment Construction

[0045] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0046] The present invention proposes a method for realizing the self-adaptive walking framework of a humanoid robot based on the CPG model, and the whole framework diagram is as attached figure 1 shown, including the following steps:

[0047] Step 1: Flat ground is the simplest environment for humanoid robots to walk, so a relatively simple CPG network can be designed to achieve flat ground walking, providing a basis for the subsequent realization of more complex adaptive walking. The rhythm signal output by the CPG is transformed and used as the torso trajectory of the end effector foot and torso of the humanoid robot, so the constructed CPG network can use fewer neurons. The end effector foot and torso of the humanoid robot are attached figure 2 shown. In this step, the CPG contains only two neurons. The mathematical expression of each neuron is:...

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Abstract

The invention discloses a method for realizing a self-adaptive walking framework of an anthropomorphic robot based on a CPG (Central Pattern Generator) model. The method comprises the following stepsof firstly, enabling a CPG network to output a reasonable rhythm control signal, so as to enable the anthropomorphic robot to walk on flat ground; designing a learning module based on a neural network, wherein the learning module is used for learning and outputting an expected rhythm compensation signal to act on the output of original CPG; finally, designing the reasonable robot feedback, so as to enable the whole control framework to output the expected rhythm control signal according to environments, thereby being suitable for various ramp environments. The method has the advantages that the problem of difficulty in production of precise and diversified rhythm signals by the CPG model in the field of bionic control of robots is solved; the practicality of the CPG model in the field of robot control is improved; the important meaning is realized for the designing of the more self-adaptive anthropomorphic robot system.

Description

technical field [0001] The invention belongs to the field of robot bionic control, in particular to a method for realizing an adaptive walking frame of a humanoid robot based on a CPG model. Background technique [0002] The movement of robots in unknown and unstructured environments has always been one of the research difficulties in the field of humanoid robot control. As a high-degree-of-freedom dynamic system, the motion control of a humanoid robot not only needs to consider the coordination between multiple joints, but also needs to process the feedback information interacting with the environment in real time. At present, the model-based method is a typical method to control the movement of humanoid robots. However, its shortcomings are also obvious. The effectiveness of this method is based on the accurate modeling of the humanoid robot body and its environment, so The workload of measurement and calculation is large, and it is difficult to compensate the modeling er...

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/163
Inventor 王勇薛喜辉陈白帆
Owner CENT SOUTH UNIV
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