NDLI: A self-tuning multi-phase CPG enabling the snake robot to adapt to environments

Content Provider	IEEE Xplore Digital Library
Author	Chaoquan Tang Shugen Ma Bin Li Yuechao Wang
Copyright Year	2011
Description	Author affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110016, China (Bin Li; Yuechao Wang) \|\| State Key Laboratory of Robotics, Automation, Chinese Academy of Sciences, Shenyang 110016, China (Chaoquan Tang) \|\| Department of Robotics, College of Science and Engineering, Ritsumeikan University, Shiga-ken 525-8577, Japan (Shugen Ma)
Abstract	Making biomimetic robots move like natural animals is an interesting problem, because this topic involves not only the low level algorithm that controls the movement of robots' bodies and limbs but also the high level control strategy that deals with different kinds of situations. Based on a certain biological assumption, a self-tuning multi-phase CPG for snake robots is proposed. This method imitates the control strategy of natural snake's movement in different environments, which enables the snake robot to move more quickly and naturally. Through kinematic and dynamic analysis of snake robots, optimal control parameters are chosen for the decision strategy. Due to the intrinsic property of the multi-phase CPG, this model can change the movement patterns and control parameters autonomously according to external information. As a result, such neural control provides a powerful but simple way to self-tune adaptable behaviors in snake robots.
Starting Page	1869
Ending Page	1874
File Size	324568
Page Count	6
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094718
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot kinematics Robot sensing systems Neurons Adaptation models Legged locomotion Mathematical model
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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