旋转拇指让机械手兼具人手灵巧与工业抓取效率
Rotograb: Combining Biomimetic Hands with Industrial Grippers using a Rotating Thumb
- 用肌腱驱动+旋转拇指设计，扩大工作空间并减少运动干扰
- 在YCB数据集上完成多种抓取与操作任务，旋转物体表现优异
- 融合遥操作与强化学习，适合复杂场景下的智能机器人应用
本研究提出Rotograb，一种基于肌腱驱动的新型机器人手，其核心创新为可旋转拇指。该设计旨在融合人手的灵巧性与工业夹具的高效性。旋转拇指显著扩展了工作空间，支持物体在握持中的自主旋转。通过特殊结构优化肌腱走线路径，降低关节间运动干扰，简化运动学模型。系统集成深度相机实现遥操作实时追踪，并采用近端策略优化（PPO）的强化学习实现自主操作。实验表明，Rotograb在处理来自YCB数据集的各类物体时表现出卓越的多样性与灵活性，尤其在握持中旋转物体方面表现突出。该设计标志着向缩小人手与工业夹具能力差距迈出重要一步，其肌腱路由与拇指旋转机制为更高水平的控制与灵巧性提供了可能。
原文摘要 · Abstract (English)
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.
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