Four-legged crawling robot CPG control system simulating lizard body structure

Abstract

The invention belongs to the field of four-legged crawling robots, in particular to a CPG neural network control system for four-legged coordinated motion control and limb-to-body coordination controlof a four-legged crawling robot simulating a lizard. The four-legged crawling robot CPG control system simulating the lizard body structure and motion characteristics comprises four parts of an advanced central nervous system, a CPG neural network system, a signal processing system and an execution system. According to the characteristics of different CPG neural network control models, differentCPG neural network control models are adopted for different parts of the body of the four-legged crawling robot, and according to the common characteristics of the CPG neural network, different CPG neural networks are connected together to finally achieve coordinated motion of the crawling robot between the limbs and between the limbs and the body.

Description

1. Technical field [0001] The invention belongs to the field of quadruped crawling robots, in particular to a CPG neural network control system for quadruped coordinated motion control and limb-trunk coordinated control of a lizard-like quadruped crawling robot. 2. Technical background [0002] Reptile-mimicking quadruped robots include both quadruped and snake-like body structure and motion control advantages over conventional quadruped robots that mimic canine or equine animals. In the water, the quadruped crawling robot imitates the movements of fish or snakes, while on the complex ground, the quadruped crawling robot can imitate the movement of reptiles on complex surfaces. Due to the high redundancy of the reptile spine, the quadruped crawler robot itself has more degrees of freedom than the degrees of freedom required to determine its position and posture, so that the quadruped crawler robot can more flexibly complete various complex tasks, and more It can adapt to th...

AI Technical Summary

Problems solved by technology

However, since the phase of the oscillator in this model is usually expressed by its sine and cosine, when building a large-scale CPG neural network model, the expression of the hopf model will be more complicated, and it is difficult for the hopf model to behave similarly to the kuramoto model by adjusting the coupling strength coefficient to achieve phase following phenomenon, so it is rarely used to achieve trunk CPG motion control

[0007] In addition, the quadruped robot turns, the general rigid body quadruped robot turns in the way of turning in situ, but there will be a phenomenon of motion stagnation in the overall movement.

However, the ordinary four-legged crawling robot needs to adjust the motion posture between the limbs to achieve steering because the torso contains fewer degrees of freedom, but the difficulty of the motion algorithm will increase.

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