抓住
机械手
人工智能
机器人学
计算机科学
人机交互
光学(聚焦)
复制
机械臂
分类
工程类
机器人
控制工程
软件工程
统计
光学
物理
数学
作者
Yuying Lin,Raveena Raj,Jia‐Yang Juang
标识
DOI:10.1088/1748-3190/ade7e1
摘要
Dexterous robotic hands have been a central focus in robotics research, aiming to replicate the versatility and functionality of the human hand. This review provides a comprehensive analysis of the latest advancements in the literature on dexterous robotic hands, covering both hardware designs and implementation methods. We categorize robotic hand dexterity into potential dexterity, grasp dexterity, and manipulation dexterity, offering a systematic framework for evaluating robotic hand performance. Various dexterous hands are then organized based on their number of digits, transmission mechanisms, actuation methods, and sensing technologies, with their dexterity compared using different evaluation criteria. Finally, we introduce various dexterous grasping and manipulation methods, including analytical approaches, machine-learning techniques, and sampling-based methods.
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