A Survey on CPG-Inspired Control Models and System Implementation | |
Yu, Junzhi1; Tan, Min1; Chen, Jian2; Zhang, Jianwei3 | |
发表期刊 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS |
2014-03-01 | |
卷号 | 25期号:3页码:441-456 |
文章类型 | Article |
摘要 | This paper surveys the developments of the last 20 years in the field of central pattern generator (CPG) inspired locomotion control, with particular emphasis on the fast emerging robotics-related applications. Functioning as a biological neural network, CPGs can be considered as a group of coupled neurons that generate rhythmic signals without sensory feedback; however, sensory feedback is needed to shape the CPG signals. The basic idea in engineering endeavors is to replicate this intrinsic, computationally efficient, distributed control mechanism for multiple articulated joints, or multi-DOF control cases. In terms of various abstraction levels, existing CPG control models and their extensions are reviewed with a focus on the relative advantages and disadvantages of the models, including ease of design and implementation. The main issues arising from design, optimization, and implementation of the CPG-based control as well as possible alternatives are further discussed, with an attempt to shed more light on locomotion control-oriented theories and applications. The design challenges and trends associated with the further advancement of this area are also summarized. |
关键词 | Bioinspired Control Central Pattern Generator (Cpg) Neural Network Parameter Tuning Robotic Applications |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | CENTRAL PATTERN GENERATOR ; COUPLED NONLINEAR OSCILLATORS ; ADAPTIVE DYNAMIC WALKING ; LOCOMOTION CONTROL ; QUADRUPED ROBOT ; SPINAL-CORD ; NEURAL OSCILLATOR ; UNPREDICTABLE ENVIRONMENT ; TRAJECTORY GENERATION ; ONLINE OPTIMIZATION |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000331985500001 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/3480 |
专题 | 复杂系统管理与控制国家重点实验室_先进机器人 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Adv Mfg Technol, Changzhou 213000, Peoples R China 3.Univ Hamburg, Dept Informat, D-22527 Hamburg, Germany |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yu, Junzhi,Tan, Min,Chen, Jian,et al. A Survey on CPG-Inspired Control Models and System Implementation[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2014,25(3):441-456. |
APA | Yu, Junzhi,Tan, Min,Chen, Jian,&Zhang, Jianwei.(2014).A Survey on CPG-Inspired Control Models and System Implementation.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,25(3),441-456. |
MLA | Yu, Junzhi,et al."A Survey on CPG-Inspired Control Models and System Implementation".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 25.3(2014):441-456. |
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