论文标题
Viko 2.0：带有Visuotactile传感器的分层壁虎启发的粘合剂
Viko 2.0: A Hierarchical Gecko-inspired Adhesive Gripper with Visuotactile Sensor
论文作者
论文摘要
带有视觉效果传感器的机器人抓手可以访问掌握任务的丰富触觉信息，但在部分用足够的抓地力的大型物体中遇到困难。虽然层次壁虎启发的粘合剂是弥合性能差距的潜在技术，但它们需要一个较大的接触区域才能有效使用。在这项工作中，我们提出了一种名为Viko 2.0的自适应壁虎抓手的新版本，该壁虎抓手有效地结合了粘合剂和视觉传感器的优势。与非层次结构相比，具有多材料设计的分层结构的正常粘附力大约增加了1.5倍，接触面积增加了两倍。集成的Visuotactile传感器捕获了层次结构的变形图像，并在24 Hz时提供了接触面积，剪切力和初始滑移检测的实时测量。握把在机器人臂上实施，以根据接触区域证明自适应抓握姿势，并抓住具有多种几何形状和纹理的对象。
Robotic grippers with visuotactile sensors have access to rich tactile information for grasping tasks but encounter difficulty in partially encompassing large objects with sufficient grip force. While hierarchical gecko-inspired adhesives are a potential technique for bridging performance gaps, they require a large contact area for efficient usage. In this work, we present a new version of an adaptive gecko gripper called Viko 2.0 that effectively combines the advantage of adhesives and visuotactile sensors. Compared with a non-hierarchical structure, a hierarchical structure with a multimaterial design achieves approximately a 1.5 times increase in normal adhesion and double in contact area. The integrated visuotactile sensor captures a deformation image of the hierarchical structure and provides a real-time measurement of contact area, shear force, and incipient slip detection at 24 Hz. The gripper is implemented on a robotic arm to demonstrate an adaptive grasping pose based on contact area, and grasps objects with a wide range of geometries and textures.
