三指自适应夹爪,能稳抓各类物体。
Grasp EveryThing (GET): 1-DoF, 3-Fingered Gripper with Tactile Sensing for Robust Grasping
- 三指呈V形排列,自适应不同形状物体
- 触觉感知误差仅1.3牛,可精准估测握力
- 设计开源,适配多种机器人平台
我们提出Grasp EveryThing (GET)夹爪,一种1-自由度、三指结构的新型夹持器,用于稳定抓取多种形状与尺寸的物体。该设计基于标准平行颚执行器,采用三个窄而锥形的指头,以两对一方式呈V形排列,能更好贴合物体几何形状并形成稳固抓握。受自相似性原理启发,该结构在宽范围物体尺寸下均具优异适应能力。指头采用参数化设计,便于根据需求调整尺寸并跨机器人平台互换使用。此外,配备刚性指甲,提升对小型物体的操作能力。通过外置摄像头实现指尖触觉传感,训练神经网络从触觉图像估计法向力,平均验证误差为1.3 N,覆盖多样几何形态。在遥操作下抓取15种物体并完成3项任务中,GET指头表现显著优于传统平面指头。所有设计文件(含带/不带触觉传感版本)均开源,兼容多种机器人平台,发布于GitHub。
原文摘要 · Abstract (English)
We introduce the Grasp EveryThing (GET) gripper, a novel 1-DoF, 3-finger design for securely grasping objects of many shapes and sizes. Mounted on a standard parallel jaw actuator, the design features three narrow, tapered fingers arranged in a two-against-one configuration, where the two fingers converge into a V-shape. The GET gripper is more capable of conforming to object geometries and forming secure grasps than traditional designs with two flat fingers. Inspired by the principle of self-similarity, these V-shaped fingers enable secure grasping across a wide range of object sizes. Further to this end, fingers are parametrically designed for convenient resizing and interchangeability across robotic embodiments with a parallel jaw gripper. Additionally, we incorporate a rigid fingernail for ease in manipulating small objects. Tactile sensing can be integrated into the standalone finger via an externally-mounted camera. A neural network was trained to estimate normal force from tactile images with an average validation error of 1.3 N across a diverse set of geometries. In grasping 15 objects and performing 3 tasks via teleoperation, the GET fingers consistently outperformed standard flat fingers. All finger designs, compatible with multiple robotic embodiments, both incorporating and lacking tactile sensing, are available on GitHub.
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