The development of robotic grippers and hands for automation aims to emulate human dexterity without sacrificing the efficiency of industrial grippers. This study introduces Rotograb, a tendon-actuated robotic hand featuring a novel rotating thumb. The aim is to combine the dexterity of human hands with the efficiency of industrial grippers. The rotating thumb enlarges the workspace and allows in-hand manipulation. A novel joint design minimizes movement interference and simplifies kinematics, using a cutout for tendon routing. We integrate teleoperation, using a depth camera for real-time tracking and autonomous manipulation powered by reinforcement learning with proximal policy optimization. Experimental evaluations demonstrate that Rotograb's rotating thumb greatly improves both operational versatility and workspace. It can handle various grasping and manipulation tasks with objects from the YCB dataset, with particularly good results when rotating objects within its grasp. Rotograb represents a notable step towards bridging the capability gap between human hands and industrial grippers. The tendon-routing and thumb-rotating mechanisms allow for a new level of control and dexterity. Integrating teleoperation and autonomous learning underscores Rotograb's adaptability and sophistication, promising substantial advancements in both robotics research and practical applications.

翻译：面向自动化的机器人夹爪与仿生手研发旨在模拟人类灵巧性的同时，不牺牲工业夹爪的效率。本研究提出Rotograb，一种采用新型旋转拇指的腱驱动仿生手，其目标是将人类手的灵巧性与工业夹爪的高效性相结合。旋转拇指扩展了工作空间并实现了手内操作。我们通过一种新颖的关节设计最小化运动干涉并简化运动学，该设计采用切口结构实现肌腱布线。我们集成了遥操作系统（采用深度相机进行实时跟踪）以及由近端策略优化强化学习驱动的自主操作系统。实验评估表明，Rotograb的旋转拇指显著提升了操作多样性与工作空间。它能够完成针对YCB数据集中物体的多种抓取与操作任务，尤其在抓握状态下旋转物体时表现优异。Rotograb标志着在弥合人类手部与工业夹爪能力差距方面迈出了重要一步。其肌腱布线机制与拇指旋转结构实现了全新水平的控制能力与灵巧性。遥操作与自主学习系统的集成凸显了Rotograb的适应性与先进性，有望为机器人学研究与实际应用带来实质性进展。