A challenging and important problem for tendon-driven multi-fingered robotic hands is to ensure grasping adaptivity while minimizing the number of actuators needed to provide human-like functionality. Inspired by the Pisa/IIT SoftHand, this paper introduces a 3D-printed, highly-underactuated, tactile-sensorized, five-finger robotic hand named the Tactile SoftHand-A, which features an antagonistic mechanism to actively open and close the hand. Our proposed dual-tendon design gives options that allow active control of specific (distal or proximal interphalangeal) joints; for example, to adjust from an enclosing to fingertip grasp or to manipulate an object with a fingertip. We also develop and integrate a new design of fully 3D-printed vision-based tactile sensor within the fingers that requires minimal hand assembly. A control scheme based on analytically extracting contact location and slip from the tactile images is used to coordinate the antagonistic tendon mechanism (using a marker displacement density map, suitable for TacTip-based sensors). We perform extensive testing of a single finger, the entire hand, and the tactile capabilities to show the improvements in reactivity, load-bearing, and manipulability in comparison to a SoftHand that lacks the antagonistic mechanism. We also demonstrate the hand's reactivity to contact disturbances including slip, and how this enables teleoperated control from human hand gestures. Overall, this study points the way towards a class of low-cost, accessible, 3D-printable, tactile, underactuated human-like robotic hands, and we openly release the designs to facilitate others to build upon this work. The designs are open-sourced at https://github.com/HaoranLi-Data/Tactile_SoftHand_A

翻译：肌腱驱动多指机器人手面临的一个关键挑战在于：在最小化执行器数量的同时确保抓取适应性，以实现类人功能。受Pisa/IIT软手的启发，本文介绍了一款名为触觉软手-A的3D打印高度欠驱动触觉传感五指机器人手，其采用拮抗机构实现手的主动开合。我们提出的双肌腱设计提供了主动控制特定关节（远端或近端指间关节）的选项，例如从包握调整至指尖抓取，或使用指尖操控物体。我们还开发并集成了一种完全3D打印的视觉触觉传感器新设计，该传感器嵌入手指内部且组装简易。基于从触觉图像中解析提取接触位置与滑动信息的控制方案（采用适用于TacTip类传感器的标记位移密度图），用于协调拮抗肌腱机构。我们通过单指测试、整手测试及触觉性能测试，系统验证了相较于无拮抗机构的软手，本手在响应速度、负载能力与可操控性方面的提升。同时展示了手部对接触干扰（包括滑动）的响应能力，以及如何通过人手姿态实现遥操作控制。总体而言，本研究为开发低成本、易获取、可3D打印的触觉欠驱动类人机器人手指明了方向，并公开设计文件以促进后续研究。设计开源地址：https://github.com/HaoranLi-Data/Tactile_SoftHand_A