论文标题
柔软的类人形手指内视觉感知的手
A Soft Humanoid Hand with In-Finger Visual Perception
论文作者
论文摘要
我们提出了一个新颖的人形五指手指软手，套件\ softhand，该手\ softhand配备了摄像头，并集成了高性能嵌入式系统，以进行视觉处理和控制。我们用内部路由的高带宽扁平电缆描述了手的致动机制和肌腱驱动的软手指设计。为了有效地从每个指尖中的相机对视觉数据进行有效的板载并行处理，我们提出了一个由现场可编程逻辑阵列（FPGA）组成的混合嵌入式体系结构和一个微控制器，该体系结构允许实现基于卷积对象分割的视觉对象段。 我们通过用一根手指进行耐久性实验来评估手部设计，并根据握力，速度和掌握成功来量化掌握性能。结果表明，该手的握力为31.8 N，手指的机械耐用性超过15.000个闭合周期。最后，我们使用五个不同的对象评估了在抓握过程的不同阶段中视觉对象分割的准确性。因此，可以实现超过90％的精度。
We present a novel underactued humanoid five finger soft hand, the KIT \softhand, which is equipped with cameras in the fingertips and integrates a high performance embedded system for visual processing and control. We describe the actuation mechanism of the hand and the tendon-driven soft finger design with internally routed high-bandwidth flat-flex cables. For efficient on-board parallel processing of visual data from the cameras in each fingertip, we present a hybrid embedded architecture consisting of a field programmable logic array (FPGA) and a microcontroller that allows the realization of visual object segmentation based on convolutional neural networks. We evaluate the hand design by conducting durability experiments with one finger and quantify the grasp performance in terms of grasping force, speed and grasp success. The results show that the hand exhibits a grasp force of 31.8 N and a mechanical durability of the finger of more than 15.000 closing cycles. Finally, we evaluate the accuracy of visual object segmentation during the different phases of the grasping process using five different objects. Hereby, an accuracy above 90 % can be achieved.
