scholarly journals Stable Walking of Humanoid Robots Using Vertical Center of Mass and Foot Motions by an Evolutionary Optimized Central Pattern Generator

10.5772/62039 ◽  
2016 ◽  
Vol 13 (1) ◽  
pp. 27 ◽  
Author(s):  
Young-Dae Hong ◽  
Ki-Baek Lee
2006 ◽  
Vol 12 (1) ◽  
pp. 63-88 ◽  
Author(s):  
Jimmy Or

Recently, there has been a lot of interest in building anthropomorphic robots. Research on humanoid robotics has focused on the control of manipulators and walking machines. The contributions of the torso towards ordinary movements (such as walking, dancing, attracting mates, and maintaining balance) have been neglected by almost all humanoid robotic researchers. We believe that the next generation of humanoid robots will incorporate a flexible spine in the torso. To meet the challenge of controlling this kind of high-degree-of-freedom robot, a new control architecture is necessary. Inspired by the rhythmic movements commonly exhibited in lamprey locomotion as well as belly dancing, we designed a controller for a simulated belly-dancing robot using the lamprey central pattern generator. Experimental results show that the proposed lamprey central pattern generator module could potentially generate plausible output patterns, which could be used for all the possible spine motions with minimized control parameters. For instance, in the case of planar spine motions, only three input parameters are required. Using our controller, the simulated robot is able to perform complex torso movements commonly seen in belly dancing as well. Our work suggests that the proposed controller can potentially be a suitable controller for a high-degree-of-freedom, flexible spine humanoid robot. Furthermore, it allows us to gain a better understanding of belly dancing by synthesis.


Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Chenpeng Yao ◽  
Chengju Liu ◽  
Li Xia ◽  
Ming Liu ◽  
Qijun Chen

Abstract To achieve adaptive gait planning of humanoid robots, a hierarchical central pattern generator (H-CPG) model with a basic rhythmic signal generation layer and a pattern formation layer is proposed to modulate the center of mass (CoM) and the online foot trajectory. The entrainment property of the CPG is exploited for adaptive walking in the absence of a priori knowledge of walking conditions, and the sensory feedback is applied to modulate the generated trajectories online to improve walking adaptability and stability. The developed control strategy is verified using a humanoid robot on sloped terrain and shows good performance.


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