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 the 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 pose estimation in the loop of optimization. The time-consuming step of 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几何测量。 人造人造人造人的软膜通过使用气动振动来加压多个弯曲室而变形。 通过调整不同舱室的气动作用来控制软膜的自由面面具有挑战性, 因为膜的形状通常由各室之间的相互作用决定。 我们利用基于 3D 的结构性光扫描器提供的视觉反馈, 开发了一种有效的算法, 以计算所有舱室的优化振动, 使软膜变形为不同目标形状的最佳近似。 我们的算法通过在优化循环中作出估计而迅速趋同。 尽可能使用 Broyden 更新来避免评估可变膜上的衍生物的耗时步骤。 我们的软机器人人造型与受控变形的效果在实验中得到了验证。