Gait Control for Biped Robot Using Fuzzy Wavelet Neural Network

2005 ◽  
pp. 133-138
Author(s):  
Pengfei Liu ◽  
Jiuqiang Han
Keyword(s):  
Neural Network ◽  
Biped Robot ◽  
Wavelet Neural Network ◽  
Gait Control ◽  
Fuzzy Wavelet Neural Network

GAIT SYNTHESIS BASED ON FWN FOR A FIVE-LINK BIPED ROBOT

2007 ◽  
Vol 05 (01) ◽  
pp. 197-211
Author(s):  
PENGFEI LIU ◽  
JIUQIANG HAN ◽  
JIANMEI MA ◽  
DONGLIN WANG
Keyword(s):  
Neural Network ◽  
Biped Robot ◽  
Wavelet Neural Network ◽  
Reference Trajectory ◽  
Back Propagation Algorithm ◽  
Double Support ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Wavelet Neural Network ◽  
Support Phase

This paper presents a new reference trajectory and a fuzzy wavelet neural network controller to synthesize the gait of a five-link biped robot when walking on the level ground. Both the single support phase (SSP) and the double support phase (DSP) are considered. The gait of the biped can be determined when the trajectories of the hip and the swing limb are designed. The trajectories of the hip and the swing limb are approximated with the time polynomial functions. The coefficients of the functions are determined by the constraint equations cast in terms of coherent physical characteristics, such as repeatability, continuity, stability, and minimization of the effect of impact. The fuzzy wavelet neural network controller is trained by error back-propagation algorithm. Given the certain gait parameters such as the step length, maximum step height, walking speed, and so on, the control scheme can generate the smooth gait profiles. The simulation results show that the designed controller can follow the reference trajectories well.

A nonlinear system identification approach based on Fuzzy Wavelet Neural Network

2015 ◽  
Vol 28 (1) ◽  
pp. 225-235 ◽  
Author(s):  
Leandro L.S. Linhares ◽  
José M. Araújo Jr. ◽  
Fábio M.U. Araújo ◽  
Takashi Yoneyama
Keyword(s):  
Neural Network ◽  
System Identification ◽  
Nonlinear System ◽  
Nonlinear System Identification ◽  
Wavelet Neural Network ◽  
Identification Approach ◽  
Fuzzy Wavelet Neural Network
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