Vertical motion control of a one legged hopping robot by using Central Pattern Generator (CPG)

2013 ◽  
Author(s):  
Arman Hadi Azahar ◽  
Chong Shin Horng ◽  
Anuar Mohamed Kassim
Keyword(s):  
Central Pattern Generator ◽  
Motion Control ◽  
Vertical Motion ◽  
Pattern Generator ◽  
Hopping Robot

Motion Control of Hydraulic Quadruped Robot Based on Central Pattern Generator

2012 ◽  
Vol 8 (1) ◽  
pp. 433-438 ◽  
Author(s):  
Bin Chen ◽  
Zhong-Cai Pei ◽  
Zhi-Yong Tang ◽  
Xiao-Qiang Guo ◽  
Hai-Xiao Zhong
Keyword(s):  
Central Pattern Generator ◽  
Motion Control ◽  
Pattern Generator ◽  
Quadruped Robot

scholarly journals Motion Control of a Gecko-like Robot Based on a Central Pattern Generator

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6045
Author(s):  
Qing Han ◽  
Feixiang Cao ◽  
Peng Yi ◽  
Tiancheng Li
Keyword(s):  
Central Pattern Generator ◽  
Motion Control ◽  
Network Model ◽  
Vertical Plane ◽  
Pattern Generator ◽  
Control Model ◽  
Rhythm Control ◽  
Complex Environments ◽  
Control Signals ◽  
Sinusoidal Function

To solve the problem of the motion control of gecko-like robots in complex environments, a central pattern generator (CPG) network model of motion control was designed. The CPG oscillation model was first constructed using a sinusoidal function, resulting in stable rhythm control signals for each joint of the gecko-like robot. Subsequently, the gecko-like robot successfully walked, crossed obstacles and climbed steps in the vertical plane, based on stable rhythm control signals. Both simulations and experiments validating the feasibility of the proposed CPG motion control model are presented.

A Feedback-Based CPG Control Method for a Single-Legged Hopping Robot

2014 ◽  
Vol 912-914 ◽  
pp. 944-947
Author(s):  
Ting Ting Wang ◽  
Fu Sheng Zha ◽  
Peng Fei Wang
Keyword(s):  
Neural Networks ◽  
Central Pattern Generator ◽  
Control Mechanism ◽  
Control Method ◽  
Pattern Generator ◽  
Robot Motion ◽  
Environment Changes ◽  
Hopping Robot ◽  
The Neural Networks ◽  
Simulation Results

Biological CPG (central pattern generator) is responsible for the generation of animals' rhythmic motion such as hopping and running. In this paper, a novel feedback-based CPG control method is proposed, in which output of the CPG network is totally activated and contained by sensory feedbacks. The network responses to environment changes quickly with multi-feedbacks included, and has strong adaption to disturbance and non-flat terrain. This control method is applied to the controlling of a single-legged hopping robot to show the effectiveness of the approach. The simulation results prove that this control mechanism closely couples environment and robot motion, and dynamically stable hopping emerges from feedbacks contained in the neural networks.

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