笛卡尔手：全线性手指的掌内操作
The Cartesian Hand: In-Hand Manipulation with All-Linear Fingers
浏览论文内容
中文总结 AI 辅助
提出笛卡尔手，一种7自由度末端执行器，通过独立抓取和相对运动的线性组合实现掌内操作，在35个物体上验证了多种操作任务，并开源软硬件设计。
中文摘要 AI 辅助
机器人操作领域日益追求具有多个关节自由度、类似人类灵巧手的设计，这提供了丰富的操作能力，但代价是机械和控制的复杂性。在另一个极端，平行夹爪简单且稳健，但在抓取物体后几乎没有操作物体的能力。操作诸如螺纹容器、制造工具和实验室仪器等关节式物体，通常需要第二个夹爪、外部固定装置或协调的机械臂运动。我们提出了笛卡尔手，一种7自由度末端执行器，通过仅使用线性运动在单个末端执行器内结合独立抓取和相对操作，重新思考灵巧操作。两个独立驱动的平行夹爪握住物体的不同部分，而四个平移指尖产生被抓取部分之间的相对运动。其与构型无关的指尖运动学允许操作由简单的线性运动原语组合而成。笛卡尔手特别适用于围绕常见机制（如螺纹、枢轴、线性导轨、柱塞和扳机）构建的物体。我们演示了在跨越实验室、制造和家庭环境的35个物体上的瓶盖开合、移液、泵送、双柄操作、螺丝刀操作、扳机驱动和抓取内重新定向。相同的操作程序可从固定基座机械臂转移到人形机器人，在那里我们演示了使用两只笛卡尔手进行的双臂实验室操作。这些结果表明，当独立抓取和相对运动被直接设计进末端执行器时，多功能掌内操作能力可以从机械简单的架构中涌现。我们将开源所有软件和硬件设计。我们的网站是此 https URL。
英文摘要
Robotic manipulation has increasingly pursued human-like dexterous hands with many articulated degrees of freedom, offering rich manipulation capabilities at the cost of mechanical and control complexity. At the other extreme, parallel grippers are simple and robust, but provide little ability to manipulate an object after grasping it. Operating articulated objects such as threaded containers, manufacturing tools, and laboratory instruments often requires a second gripper, an external fixture, or coordinated arm motion. We introduce the Cartesian Hand, a 7-DoF end-effector that rethinks dexterous manipulation by combining independent grasping and relative manipulation within a single end-effector using only linear motion. Two independently actuated parallel grippers hold different parts of an object, while four translating fingertips generate relative motion between the grasped parts. Its configuration-independent fingertip kinematics allow manipulation to be composed from simple linear motion primitives. The Cartesian Hand is particularly suited to objects structured around common mechanisms such as threads, pivots, linear guides, plungers, and triggers. We demonstrate cap opening and closing, pipetting, pumping, two-handle manipulation, screwdriving, trigger actuation, and in-grasp reorientation across 35 objects spanning laboratory, manufacturing, and household settings. The same manipulation procedures transfer from a fixed-base robot arm to a humanoid, where we demonstrate bimanual laboratory manipulation using two Cartesian Hands. These results show that versatile in-hand manipulation capability can emerge from a mechanically simple architecture when independent grasping and relative motion are designed directly into the end-effector. We will open-source all software and hardware design. Our website is https://generalroboticslab.com/cartesian_handv1.
发表机构
- Duke University（杜克大学）
机构由 AI 辅助整理，请以论文原文为准。
