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
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
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.
