[2018-Vol.15-Issue 2]Multi-Layered CPG for Adaptive Walking of Quadruped Robots
Time: 2018-03-28 10:05  Click:429
Journal of Bionic Engineering
 
Volume 15, Issue 2, March 2018, Pages 341-355.
 
Chengju Liu*, Li Xia, Changzhu Zhang, Qijun Chen
School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
 
 Abstract  This work concerns biped adaptive walking control on slope terrains with online trajectory generation. In terms of the lack of satis-factory performances of the traditional simplified single-layered Central Pattern Generator (CPG) model in engineering applications where robots face unknown environments and access feedback, this paper presents a Multi-Layered CPG (ML-CPG) model based on a half-center CPG model. The proposed ML-CPG model is used as the underlying low-level controller for a quadruped robot to generate adaptive walking patterns. Rhythm-generation and pattern formation interneurons are modeled to promptly generate motion rhythm and patterns for motion sequence control, while motoneurons are modeled to control the output strength of the joint in real time according to feedback. Referring to the motion control mechanisms of animals, a control structure is built for a quadruped robot. Multi-sensor models abstracted from the neural reflexes of animals are involved in all the layers of neurons through various feedback paths to achieve adaptability as well as the coordinated motion control of a robot’s limbs. The simulation experiments verify the effectiveness of the pre-sented ML-CPG and multi-layered reflexes strategy.
 
Key words: Multi-Layered CPG (ML-CPG)      biological reflex      quadruped robot      adaptive walking  
 

 

Home| News| Research Progress| Events & Meetings| Resources| Membership| Contact Privacy Policy Terms of use

Address: 1201 Administrative Building, Jilin University, 2699 Qianjin Street, Changchun 130012, P. R. China

Copyright © 2018 International Society of Bionic Engineering All Rights Reserved