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Quadruped robot movement track control method based on PSO-PD (Particle Swarm Optimization-PD) neural network

A quadruped robot, robot motion technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., to achieve the effect of good control requirements, high control accuracy, and satisfying control requirements

Active Publication Date: 2017-06-23
QILU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it is still impossible to achieve continuous and accurate nonlinear motion trajectory control for robots

Method used

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  • Quadruped robot movement track control method based on PSO-PD (Particle Swarm Optimization-PD) neural network
  • Quadruped robot movement track control method based on PSO-PD (Particle Swarm Optimization-PD) neural network
  • Quadruped robot movement track control method based on PSO-PD (Particle Swarm Optimization-PD) neural network

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Embodiment

[0100] A method for controlling motion trajectory of a quadruped robot based on PSO-PD neural network, comprising:

[0101] (1) According to the trajectory of the quadruped robot and the preset step size, the target landing point of the center of gravity of the quadruped robot on the trajectory is obtained, that is, the coordinates of the center of gravity of the quadruped robot on the trajectory; it is relative to the actual result spoken.

[0102] (2) The target landing point of the center of gravity of the quadruped robot obtained in step (1) on the motion trajectory, and the real-time feedback position of the center of gravity of the torso (y x ,y y ) into the input layer of the PD neural network model; enter the first hidden layer of the PD neural network model after linear transformation, and perform proportional and differential operations in the first hidden layer; enter the second hidden layer of the PD neural network model after linear transformation again Hidden l...

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Abstract

The invention relates to a quadruped robot movement track control method based on a PSO-PD (Particle Swarm Optimization-PD) neural network. The quadruped robot movement track control method comprises the following steps: (1) calculating a target falling point of a robot on a movement track; (2) inputting the target falling point and a feedback body gravity center position into an input layer of the PSO-PD neural network, performing linear conversion, inputting into a first hidden layer, performing ratio calculation and differential operation, performing linear conversion, inputting into a second hidden layer, and acquiring instruction displacement in an x direction and a y direction, inputting into a third hidden layer, calculating an instruction displacement distance, instructing a body direction, inputting into a fifth layer, performing foot tract control and steering control on a quadruped robot, inputting into a sixth layer, adjusting the posture of the quadruped robot in case of disturbance, inputting into a seventh layer, calculating the body direction and the body gravity center position of the quadruped robot, feeding back the body direction to the fifth layer, and feeding back the body gravity center position to the input layer. The quadruped robot movement track control method has relatively good non-linear decoupling control capability, is precise in control and good in stability, and has relatively good anti-interference properties.

Description

technical field [0001] The invention relates to a method for controlling the trajectory of a robot, in particular to a method for controlling the trajectory of a quadruped robot based on a PSO-PD neural network. Background technique [0002] With the rapid development of science and technology, robotics is increasingly used in complex environments. Compared with wheeled or tracked robots, legged robots have certain advantages in moving in unstructured environments. Compared with other multi-legged walking robots, the quadruped robot has the advantages of simple structure and stable motion, so it has high research significance and application value. When working in a complex environment, the robot runs along a preset trajectory. It can pass through each working point with the fastest speed and the lowest energy consumption, and at the same time avoid various obstacles and other factors that affect the stable operation. Therefore, it is of great significance to study the tr...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 孙涛靳欣李凡冰
Owner QILU UNIV OF TECH
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