scholarly journals Feasibility Check of an Assist System Through the Simulation of Bipedal Walking Using a CPG

2012 ◽  
Vol 24 (4) ◽  
pp. 657-665
Author(s):  
Tomohito Takubo ◽  
◽  
Yohei Fukano ◽  
Kenichi Ohara ◽  
Yasushi Mae ◽  
...  
Keyword(s):  
Pressure Sensor ◽  
Pattern Generator ◽  
Pattern Generation ◽  
Bipedal Walking ◽  
Human Walking ◽  
Trajectory Data ◽  
Body Dimension ◽  
Walking Pattern ◽  
Walking Pattern Generation ◽  
Mobile Base

A wearable mobile-base Walking Assist System (WAS) is simulated in this paper with the bipedal simulator we developed. The simulator employs a Central Pattern Generator (CPG) for bipedal walking pattern generation. The CPG-based walking pattern is one of the candidates for simulating human walking. Average Japanese body dimension data is applied to the bipedal model so that walking efficiency can be evaluated using the simulator. The effectiveness of the proposed simulator is confirmed by comparing real human walking and simulated walking in terms of the shape of the swing leg trajectory, data from the pressure sensor, and the feasibility of the prototype WAS. A prototype is developed and experimental results show the effectiveness of the bipedal simulator.

scholarly journals Bipedal walking pattern generation and control for humanoid robot with bivariate stability margin optimization

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401880088
Author(s):  
Liang Yang ◽  
Zhi Liu ◽  
Yong Chen
Keyword(s):  
Neural Networks ◽  
Vector Function ◽  
Random Vector ◽  
Humanoid Robot ◽  
Stability Margin ◽  
Pattern Generation ◽  
Bipedal Walking ◽  
Walking Pattern ◽  
Control Scheme ◽  
Walking Pattern Generation

This article concentrates on the problem of walking pattern generation and online control for humanoid robot. However, it is challenging and thus still remains open so far in the field of bipedal locomotion control. In this article, we solve this problem by proposing a bivariate-stability-margin-based control scheme, in which a random vector function-link neural networks mechanism is additionally contained. By utilizing opposition-based learning algorithm to generate walking patterns and designing random vector function-link neural networks for compensating the combination of zero-moment point error and modeling error, the new walking controller exhibits good performance. Moreover, a bivariate-stability-margin-based fuzzy logic system is proposed to assign a weight to each training sample according to locomotion stability. With these results, a walking control system is successfully established and experiments validate the proposed control scheme.

scholarly journals Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot

2020 ◽  
Vol 26 (12) ◽  
pp. 1-20
Author(s):  
Ali Fawzi Abdul Kareem ◽  
Ahmed Abdul Hussein Ali
Keyword(s):  
Degrees Of Freedom ◽  
Pattern Generation ◽  
Driver Model ◽  
Bipedal Walking ◽  
Time Interval ◽  
Bipedal Robot ◽  
Walking Pattern ◽  
Walking Pattern Generation ◽  
Arduino Microcontroller ◽  
Support Phase

Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking robot. The results showed that this driver confirms the faster response than the Arduino microcontroller in walking the bipedal robot. The walking pattern generation results showed that the step height for 17 degrees of freedom bipedal robot increases approximately (20%) than 10 degrees of freedom bipedal robot, which decreases the step period by about (7%). Also, the time interval of the double support phase for 17 degrees of freedom bipedal robot increases approximately (11%) with decreases step length approximately (33% on X-axis) and (16% on Z-axis).  

scholarly journals 1402 Walking Pattern Generation of a Two-legged Robot by CPG and Optimization of Walking

2007 ◽  
Vol 2007.82 (0) ◽  
pp. _14-2_
Author(s):  
Yusuke SAITO ◽  
Kiyoshi OGAWA ◽  
Yogo TAKADA ◽  
Tomoyuki WAKISAKA
Keyword(s):  
Pattern Generation ◽  
Legged Robot ◽  
Walking Pattern ◽  
Walking Pattern Generation
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