Kashef Tabrizian Seyedreza, Alabiso Walter, Shaukat Usman, Terryn Seppe, Rossegger Elisabeth, Brancart Joost, Legrand Julie, Schlögl Sandra, Vanderborght Bram
Brubotics, Vrije Universiteit Brussel (VUB) and Imec, Brussels, Belgium.
Polymer Competence Center Leoben GmbH, Leoben, Austria.
Front Robot AI. 2023 Jul 12;10:1206579. doi: 10.3389/frobt.2023.1206579. eCollection 2023.
The variability in the shapes and sizes of objects presents a significant challenge for two-finger robotic grippers when it comes to manipulating them. Based on the chemistry of vitrimers (a new class of polymer materials that have dynamic covalent bonds, which allow them to reversibly change their mechanical properties under specific conditions), we present two designs as 3D-printed shape memory polymer-based shape-adaptive fingertips (SMP-SAF). The fingertips have two main properties needed for an effective grasping. First, the ability to adapt their shape to different objects. Second, exhibiting variable rigidity, to lock and retain this new shape without the need for any continuous external triggering system. Our two design strategies are: 1) A curved part, which is suitable for grasping delicate and fragile objects. In this mode and prior to gripping, the SMP-SAFs are straightened by the force of the parallel gripper and are adapted to the object by shape memory activation. 2) A straight part that takes on the form of the objects by contact force with them. This mode is better suited for gripping hard bodies and provides a more straightforward shape programming process. The SMP-SAFs can be programmed by heating them up above glass transition temperature (54°C) via Joule-effect of the integrated electrically conductive wire or by using a heat gun, followed by reshaping by the external forces (without human intervention), and subsequently fixing the new shape upon cooling. As the shape programming process is time-consuming, this technique suits adaptive sorting lines where the variety of objects is not changed from grasp to grasp, but from batch to batch.
物体形状和尺寸的变化给双指机器人夹具在操纵它们时带来了重大挑战。基于 Vitrimers（一类新型聚合物材料，具有动态共价键，使其能够在特定条件下可逆地改变其机械性能）的化学原理，我们提出了两种基于 3D 打印形状记忆聚合物的形状自适应指尖（SMP-SAF）设计。这些指尖具有有效抓取所需的两个主要特性。首先，能够使其形状适应不同物体。其次，表现出可变的刚度，以锁定并保持这种新形状，而无需任何连续的外部触发系统。我们的两种设计策略是：1）一个弯曲部分，适用于抓取精致易碎的物体。在这种模式下，在抓取之前，SMP-SAF 通过平行夹具的力伸直，并通过形状记忆激活适应物体。2）一个直的部分，通过与物体的接触力呈现物体的形状。这种模式更适合抓取刚体，并提供更直接的形状编程过程。SMP-SAF 可以通过集成的导电丝的焦耳效应或使用热风枪将其加热到玻璃化转变温度（54°C）以上进行编程，然后在外力作用下（无需人工干预）重新塑形，随后在冷却时固定新形状。由于形状编程过程耗时，这种技术适用于自适应分拣线，在这种分拣线中，物体的种类不是从一次抓取到另一次抓取发生变化，而是从一批到另一批发生变化。
