Smart Robotic Surfaces - Multi-scale Actuation of Topographies for Adaptive Adhesion

当章鱼握住一个物体时，它既通过包裹整个触须来抓握(宏观上)，也会在局部用吸盘环粘住，然后扭转这种粘连以释放。或者想想这种苍蝇，它利用双脚的可逆粘着来着陆、保持并迅速脱离表面。许多生物体都有机制，通过动态的局部结构变化(脚、皮肤、爪子)，可逆地改变粘附性的界面强度，用于攀爬、握持/释放、摩擦控制和运动。具有可切换附着力的工程材料的例子很少。但任何使用接触粘合的技术系统，如机器人、传送带、手套和医疗器械，都可以通过可逆地改变其表面的界面粘合强度(或摩擦)来从根本上改变。制造中的传送带可以更好地操纵物体，尼龙搭扣可以被打开/关闭，可切换的脚垫可以使机器人攀登，智能手套可以主动调整其抓地力，或者新一代医疗设备可以在手术中连接和释放软组织。 该方案旨在通过微米级和毫米级表面形貌(微柱)的驱动(移动和定位)来开发具有可切换控制和动态优化粘接强度的材料。我们开发了动态微柱阵列(DMA)，利用气压(气动)或水压(液压)来控制与表面的机械粘合。压力变化会使微柱变形，从而使其向外膨胀或向内收缩，并抓取表面。我们的方法使这种微型柱子的移动可以数字控制，使它们成为机器人表面，因为它们的移动和属性可以编程。我们还计划通过感觉反馈来控制它们，感受它们附着在表面上的成功或失败。我们的目标是通过这种局部控制来更好地理解机械粘连的机制。传感将允许粘合DMA层优化其整体粘合强度，并主动应对粘合失败(滑动)。将测试机器学习算法以响应压力传感信息。这种动态粘合的方法以前从未被演示过。这种方法的潜在应用可能对机器人和医学技术具有非常重要的意义，我们将特别探索它在皮肤粘连方面的应用。

When an octopus holds an object, it both grips (macroscopically) by wrapping its whole tentacle, but also locally adheres with sucker rings, before reversing that adhesion for release. Or consider the fly that uses reversible adhesion of its feet to land, hold and then quickly detach from surfaces. A wide range of organisms have mechanisms to reversibly change interfacial strength of adhesion, through dynamic, local structural change (of feet, skin, claws), for climbing, gripping/release, frictional control and locomotion. There are few examples of engineered materials with switchable adhesion. But any technological system using contact adhesion, such as robots, conveyors, gloves and medical devices, could be radically changed by the ability to reversibly change the interfacial adhesion strength (or friction) of their surfaces. Conveyors in manufacturing could better manipulate objects, Velcro could be switched on/off, switchable foot pads could enable climbing robots, a smart' glove could actively tune its grip, or a new generation of medical devices could attach and release from soft tissue in surgery. This proposal aims to develop materials with switchable control and dynamic optimization of adhesion strength through the actuation (movement and positioning) of micrometer and millimeter scale surface topographies (microposts). We have developed dynamic micropost arrays' (DMA) to control mechanical adhesion to surfaces, using air pressure (pneumatics) or water pressure (hydraulics). The pressure change can deform the microposts to make them expand out or retract in and grip surfaces as a result. Our approach enables this micropost movement to be controlled digitally, to make them robotic surfaces', as their movement and properties can be programmed. We also plan to control them through sensory feedback, to feel' their successful or failed adhesion to a surface. We aim to better understand mechanisms of mechanical adhesion through this local control. Sensing will allow an adhesive DMA layer to optimize its overall adhesion strength, and actively respond to an adhesive failure (slipping). Machine learning algorithms will be tested to respond to pressure sensing information. This approach to dynamic adhesion has not been demonstrated before. Potential applications of this approach could be very significant for technologies in robotics and medicine, and we will explore its application to skin adhesion in particular.