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作 者:张智超 张家铭 周丽丽 ZHANG Zhi-chao;ZHANG Jia-ming;ZHOU Li-li(Institute of Intelligent Manufacturing,Heilongjiang Academy of Sciences,Harbin 150090 China)
机构地区:[1]黑龙江省科学院智能制造研究所,黑龙江哈尔滨150090
出 处:《自动化技术与应用》2025年第3期176-179,共4页Techniques of Automation and Applications
摘 要:为了提升生理辅助协同系统的适应性和自主性,本文采用类脑计算方式模仿人脑工作原理,对系统进行感知、决策协同控制,使仿生系统更加智能化。为了使系统更加仿生、高效,本系统模拟高级中枢和低级中枢的神经系统模式,将类脑计算控制和中枢模式发生器(CPG)相结合,使系统具有更高级的认知能力和更稳定的运动模式。为了提高系统的精准性,系统引入肌电信号作为反馈信号,为协同控制系统提供精确的运动意图感知,优化了系统控制策略。该智能协同系统将类脑计算控制和中枢模式发生器结合,同时引入肌电信号作为反馈,是类脑技术、肌电反馈技术、控制技术发展的融合,是脑科学、神经科学、运动学、计算机科学等多科的交叉融合,为仿生机器人、康复医疗、智能制造等领域发展提供了新的支持。To enhance the adaptability and autonomy of the physiologically assisted collaborative system,this paper adopts brain-like computing to mimic the working principle of the human brain,enabling perception and decision-making collaborative control of the system and making the bionic system more intelligent.To make the system more biomimetic and efficient,this system simulates the nervous system model of the higher and lower centers,combining brain-like computing control with a Central Pattern Generator(CPG).This allows the system to possess more advanced cognitive abilities and more stable movement patterns.To improve the precision of the system,electromyography signals are introduced as feedback signals,providing accurate perception of movement intention for the collaborative control system and optimizing the system control strategy.This intelligent collaborative system combines brain-like computing control with a Central Pattern Generator while introducing electromyography signals as feedback.It represents a convergence of new developments in brain-like technology,electromyography feedback technology,and control technology,and is a multidisciplinary crossover integration of brain science,neuroscience,kinematics,and computer science.This provides new support for the development of fields such as bionic robots,rehabilitation medicine,and intelligent manufacturing.
关 键 词:类脑计算 肌电反馈 中枢模式发生器 仿生协同系统
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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