To be used as five-fingered myoelectric hands in daily living, robotic hands must be lightweight with the size of human hands. In addition, they must possess the DoFs （degrees of freedom） and high grip force similar...To be used as five-fingered myoelectric hands in daily living, robotic hands must be lightweight with the size of human hands. In addition, they must possess the DoFs （degrees of freedom） and high grip force similar to those of human hands. Balancing these requirements involves a trade-off; ideal robotic hands have yet to sufficiently satisfy both requirements. Herein, a power allocation mechanism is proposed to improve the grip force without increasing the size or weight of robotic hands by using redundant DoFs during pinching motions. Additionally, this mechanism is applied to an actual five-fingered myoelectric hand, which produces seven types of motions necessary for activities of daily living and realizes a -60% improvement in fingertip force, allowing three fingers to pinch objects exceeding 1 kg.展开更多
Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advanceme...Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advancements in visual and tactile perception,have demonstrated significant advantages in addressing this issue.However,coping with the inevitable uncertainty caused by unstructured and dynamic environments in human-like dexterous manipulation tasks,especially for anthropomorphic five-fingered hands,remains an open problem.In this paper,we present a focused review of human-like dexterous manipulation for anthropomorphic five-fingered hands.We begin by defining human-like dexterity and outlining the tasks associated with human-like robot dexterous manipulation.Subsequently,we delve into anthropomorphism and anthropomorphic five-fingered hands,covering definitions,robotic design,and evaluation criteria.Furthermore,we review the learning methods for achieving human-like dexterity in anthropomorphic five-fingered hands,including imitation learning,reinforcement learning and their integration.Finally,we discuss the existing challenges and propose future research directions.This review aims to stimulate interest in scientific research and future applications.展开更多
以适用于空间在轨服务的腱驱动五指灵巧手为研究对象,设计具有一定实时性的控制系统.为满足腱驱动灵巧手多指操作对同步性和实时性的特殊要求,提出基于RTX(real time extension)共享内存的模块化软件架构,可集成人机交互、虚拟显示、遥...以适用于空间在轨服务的腱驱动五指灵巧手为研究对象,设计具有一定实时性的控制系统.为满足腱驱动灵巧手多指操作对同步性和实时性的特殊要求,提出基于RTX(real time extension)共享内存的模块化软件架构,可集成人机交互、虚拟显示、遥操作以及数据传输等模块,具有扩展性好、结构清晰、传输效率高的优点.针对腱驱动耦合的问题,提出关节空间到腱空间的解耦矩阵,并据此给出实时多指协调运动控制方法,以确保各手指同时到达期望位置,减小腱驱动迟滞造成的不利影响.最后通过多指灵巧抓取以及遥操作实验,验证所提控制系统的稳定性、可靠性.展开更多
文摘To be used as five-fingered myoelectric hands in daily living, robotic hands must be lightweight with the size of human hands. In addition, they must possess the DoFs （degrees of freedom） and high grip force similar to those of human hands. Balancing these requirements involves a trade-off; ideal robotic hands have yet to sufficiently satisfy both requirements. Herein, a power allocation mechanism is proposed to improve the grip force without increasing the size or weight of robotic hands by using redundant DoFs during pinching motions. Additionally, this mechanism is applied to an actual five-fingered myoelectric hand, which produces seven types of motions necessary for activities of daily living and realizes a -60% improvement in fingertip force, allowing three fingers to pinch objects exceeding 1 kg.
基金supported in part by the National Natural Science Foundation of China(91748131,62006229,and 61771471)in part by Young Scientists Fund of the National Natural Science Foundation of China(62303454)+1 种基金in part by the Strategic Priority Research Program of Chinese Academy of Science(XDB32050106)in part by the InnoHK Project.
文摘Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advancements in visual and tactile perception,have demonstrated significant advantages in addressing this issue.However,coping with the inevitable uncertainty caused by unstructured and dynamic environments in human-like dexterous manipulation tasks,especially for anthropomorphic five-fingered hands,remains an open problem.In this paper,we present a focused review of human-like dexterous manipulation for anthropomorphic five-fingered hands.We begin by defining human-like dexterity and outlining the tasks associated with human-like robot dexterous manipulation.Subsequently,we delve into anthropomorphism and anthropomorphic five-fingered hands,covering definitions,robotic design,and evaluation criteria.Furthermore,we review the learning methods for achieving human-like dexterity in anthropomorphic five-fingered hands,including imitation learning,reinforcement learning and their integration.Finally,we discuss the existing challenges and propose future research directions.This review aims to stimulate interest in scientific research and future applications.
文摘以适用于空间在轨服务的腱驱动五指灵巧手为研究对象,设计具有一定实时性的控制系统.为满足腱驱动灵巧手多指操作对同步性和实时性的特殊要求,提出基于RTX(real time extension)共享内存的模块化软件架构,可集成人机交互、虚拟显示、遥操作以及数据传输等模块,具有扩展性好、结构清晰、传输效率高的优点.针对腱驱动耦合的问题,提出关节空间到腱空间的解耦矩阵,并据此给出实时多指协调运动控制方法,以确保各手指同时到达期望位置,减小腱驱动迟滞造成的不利影响.最后通过多指灵巧抓取以及遥操作实验,验证所提控制系统的稳定性、可靠性.
