论文标题

基于晶格的形状跟踪和弹性对象的致棉

Lattice-based shape tracking and servoing of elastic objects

论文作者

Shetab-Bushehri, Mohammadreza, Aranda, Miguel, Mezouar, Youcef, Ozgur, Erol

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

In this paper, we propose a general unified tracking-servoing approach for controlling the shape of elastic deformable objects using robotic arms. Our approach works by forming a lattice around the object, binding the object to the lattice, and tracking and servoing the lattice instead of the object. This makes our approach have full 3D control over deformable objects of any general form (linear, thin-shell, volumetric). Furthermore, it decouples the runtime complexity of the approach from the objects' geometric complexity. Our approach is based on the As-Rigid-As-Possible (ARAP) deformation model. It requires no mechanical parameter of the object to be known and can drive the object toward desired shapes through large deformations. The inputs to our approach are the point cloud of the object's surface in its rest shape and the point cloud captured by a 3D camera in each frame. Overall, our approach is more broadly applicable than existing approaches. We validate the efficiency of our approach through numerous experiments with deformable objects of various shapes and materials (paper, rubber, plastic, foam). Experiment videos are available on the project website: https://sites.google.com/view/tracking-servoing-approach.

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