This paper presents a novel soft robotic system for a deformable mannequin that can be employed to physically realize the 3D geometry of different human bodies. The soft membrane on a mannequin is deformed by inflating several curved chambers using pneumatic actuation. Controlling the freeform surface of a soft membrane by adjusting the pneumatic actuation in different chambers is challenging as the membrane's shape is commonly determined by interaction between all chambers. Using vision feedback provided by a structured-light based 3D scanner, we developed an efficient algorithm to compute the optimized actuation of all chambers which could drive the soft membrane to deform into the best approximation of different target shapes. Our algorithm converges quickly by including the step of pose estimation in the loop of optimization, and the time-consuming step for evaluating derivatives on the deformable membrane is avoided by using the Broyden update when possible. The effectiveness of our soft robotic mannequin with controlled deformation has been verified in experiments.
翻译:本文展示了一个新的软机器人系统, 用于对不同人体进行3D几何物理测量。 人猿上的软膜通过使用气动振动来加压多个弯曲室而变形。 通过调整不同室室的气动作用来控制软膜的自由表面是困难的, 因为膜的形状通常由所有室室之间的相互作用决定。 我们利用基于 3D 扫描器的结构灯光提供的视觉反馈, 开发了一种有效的算法, 以计算所有室室的优化振动, 使软膜变形为不同目标形状的最佳近似。 我们的算法快速趋同, 在优化循环中包括姿势估计的步骤, 并且尽可能使用 Broyden 更新来避免评估变形膜上衍生物的耗时步骤。 我们的软机器人元件在受控变形方面的有效性在实验中得到了验证。