Full-body joint trajectory generation using an evolutionary central pattern generator for stable bipedal walking

Author(s):  
Chang-Soo Park ◽  
Young-Dae Hong ◽  
Jong-Hwan Kim
2021 ◽  
Vol 15 ◽  
Author(s):  
Dai Owaki ◽  
Shun-ya Horikiri ◽  
Jun Nishii ◽  
Akio Ishiguro

Despite the appealing concept of central pattern generator (CPG)-based control for bipedal walking robots, there is currently no systematic methodology for designing a CPG-based controller. To remedy this oversight, we attempted to apply the Tegotae approach, a Japanese concept describing how well a perceived reaction, i.e., sensory information, matches an expectation, i.e., an intended motor command, in designing localised controllers in the CPG-based bipedal walking model. To this end, we developed a Tegotae function that quantifies the Tegotae concept. This function allowed incorporating decentralised controllers into the proposed bipedal walking model systematically. We designed a two-dimensional bipedal walking model using Tegotae functions and subsequently implemented it in simulations to validate the proposed design scheme. We found that our model can walk on both flat and uneven terrains and confirmed that the application of the Tegotae functions in all joint controllers results in excellent adaptability to environmental changes.


2012 ◽  
Vol 60 (2) ◽  
pp. 182-198 ◽  
Author(s):  
Mostafa Ajallooeian ◽  
Majid Nili Ahmadabadi ◽  
Babak Nadjar Araabi ◽  
Hadi Moradi

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