Locomotion Control for Quadruped Robot Combining Central Pattern Generators with Virtual Model Control

Author(s):  
Xiang Wang ◽  
Houde Liu ◽  
Bin Liang ◽  
Xueqian Wang ◽  
Jun Yang
Author(s):  
Thirawat Chuthong ◽  
Binggwong Leung ◽  
Kawee Tiraborisute ◽  
Potiwat Ngamkajornwiwat ◽  
Poramate Manoonpong ◽  
...  

2011 ◽  
Vol 2 (1) ◽  
pp. 39-62 ◽  
Author(s):  
Miguel Oliveira ◽  
Cristina P. Santos ◽  
Lino Costa ◽  
Ana Rocha ◽  
Manuel Ferreira

In this work, the authors propose a combined approach based on a controller architecture that is able to generate locomotion for a quadruped robot and a global optimization algorithm to generate head movement stabilization. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs) that are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approach allows for explicitly specified parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated oscillations according to changes in these parameters. The overall idea is to generate head movement opposed to the one induced by locomotion, such that the head remains stabilized. Thus, in order to achieve this desired head movement, it is necessary to appropriately tune the CPG parameters. Three different global optimization algorithms search for this best set of parameters. In order to evaluate the resulting head movement, a fitness function based on the Euclidean norm is investigated. Moreover, a constraint-handling technique based on tournament selection was implemented.


2015 ◽  
Vol 30 (4) ◽  
pp. 284-297 ◽  
Author(s):  
Guoteng Zhang ◽  
Xuewen Rong ◽  
Chai Hui ◽  
Yibin Li ◽  
Bin Li

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141988528
Author(s):  
Yasushi Habu ◽  
Keiichiro Uta ◽  
Yasuhiro Fukuoka

We aim to design a neuromorphic controller for the locomotion of a quadruped robot with muscle-driven leg mechanisms. To this end, we use a simulated cat model; each leg of the model is equipped with three joints driven by six muscle models incorporating two-joint muscles. For each leg, we use a two-level central pattern generator consisting of a rhythm generation part to produce basic rhythms and a pattern formation part to synergistically activate a different set of muscles in each of the four sequential phases (swing, touchdown, stance, and liftoff). Conventionally, it was difficult for a quadruped model with such realistic neural systems and muscle-driven leg mechanisms to walk even on flat terrain, but because of our improved neural and mechanical components, our quadruped model succeeds in reproducing motoneuron activations and leg trajectories similar to those in cats and achieves stable three-dimensional locomotion at a variety of speeds. Moreover, the quadruped is capable of walking upslope and over irregular terrains and adapting to perturbations, even without adjusting the parameters.


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