The neural-based approaches inspired by biological neural mechanisms of locomotion are becoming increasingly popular in robot control.This paper investigates a systematic method to formulate a Central Pattern Generato...The neural-based approaches inspired by biological neural mechanisms of locomotion are becoming increasingly popular in robot control.This paper investigates a systematic method to formulate a Central Pattern Generator(CPG) based control model for mul-timodal swimming of a multi-articulated robotic fish with flexible pectoral fins.A CPG network is created to yield diverse swim-ming in three dimensions by coupling a set of nonlinear neural oscillators using nearest-neighbor interactions.In particular,a sensitivity analysis of characteristic parameters and a stability proof of the CPG network are given.Through the coordinated con-trol of the joint CPG,caudal fin CPG,and pectoral fin CPG,a diversity of swimming modes are defined and successfully imple-mented.The latest results obtained demonstrate the effectiveness of the proposed method.It is also confirmed that the CPG-based swimming control exhibits better dynamic invariability in preserving rhythm than the conventional body wave method.展开更多
人类从胎儿开始,动作行为就以自发的神经活动为基础,脑干和脊髓的神经网络活动受到脊髓上活动的调节。脊髓上活动首先由皮层板引起,随之引起动作的变化,起初这些动作的变化是为探索服务,其相关的传入信息主要用于塑造神经系统的发育。随...人类从胎儿开始,动作行为就以自发的神经活动为基础,脑干和脊髓的神经网络活动受到脊髓上活动的调节。脊髓上活动首先由皮层板引起,随之引起动作的变化,起初这些动作的变化是为探索服务,其相关的传入信息主要用于塑造神经系统的发育。随后,动作的变化逐渐开始适应,随着年龄和试错探索的增加,婴幼儿适应后的有效动作发展能力得到了显著的提升。文章从人类大脑进化与动作发展的某些启示出发,围绕动态系统理论(dynamic systems theory, DST)和神经元群选择理论(neuronal group selection theory, NGST)进行理论溯源,提出动作发展的循证轨迹。在探索理论的同时,文章对新生儿可穿戴式运动监测设备的研制,胎动(fetal movement, FM)的监测与应用以及基本动作技能(fundamental Motor Skill, FMS)的发展与学习三个应用研究领域进行了局部展望,这些领域着眼于“脑与动作的双向构建”,将有助于我们了解人类动作发展与脑科学之间的联系,从而期望开辟新的研究领域来更好地理解动作发展的内生机制。展开更多
基金the National Natural Science Foundation of China (60775053,61075102)in part by the Beijing Natural Science Foundation (4102063,4122084)
文摘The neural-based approaches inspired by biological neural mechanisms of locomotion are becoming increasingly popular in robot control.This paper investigates a systematic method to formulate a Central Pattern Generator(CPG) based control model for mul-timodal swimming of a multi-articulated robotic fish with flexible pectoral fins.A CPG network is created to yield diverse swim-ming in three dimensions by coupling a set of nonlinear neural oscillators using nearest-neighbor interactions.In particular,a sensitivity analysis of characteristic parameters and a stability proof of the CPG network are given.Through the coordinated con-trol of the joint CPG,caudal fin CPG,and pectoral fin CPG,a diversity of swimming modes are defined and successfully imple-mented.The latest results obtained demonstrate the effectiveness of the proposed method.It is also confirmed that the CPG-based swimming control exhibits better dynamic invariability in preserving rhythm than the conventional body wave method.
文摘人类从胎儿开始,动作行为就以自发的神经活动为基础,脑干和脊髓的神经网络活动受到脊髓上活动的调节。脊髓上活动首先由皮层板引起,随之引起动作的变化,起初这些动作的变化是为探索服务,其相关的传入信息主要用于塑造神经系统的发育。随后,动作的变化逐渐开始适应,随着年龄和试错探索的增加,婴幼儿适应后的有效动作发展能力得到了显著的提升。文章从人类大脑进化与动作发展的某些启示出发,围绕动态系统理论(dynamic systems theory, DST)和神经元群选择理论(neuronal group selection theory, NGST)进行理论溯源,提出动作发展的循证轨迹。在探索理论的同时,文章对新生儿可穿戴式运动监测设备的研制,胎动(fetal movement, FM)的监测与应用以及基本动作技能(fundamental Motor Skill, FMS)的发展与学习三个应用研究领域进行了局部展望,这些领域着眼于“脑与动作的双向构建”,将有助于我们了解人类动作发展与脑科学之间的联系,从而期望开辟新的研究领域来更好地理解动作发展的内生机制。
