论文标题
强大的枢纽：使用双重优化利用摩擦稳定性
Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization
论文作者
论文摘要
可推广的操作要求机器人能够与新颖的对象和环境进行交互。这项要求使操作极具挑战性，因为机器人必须推理与物体物理特性不确定性的复杂摩擦相互作用。在本文中，我们研究了在不确定性存在下控制枢转操作的强大优化。我们提供了有关如何利用摩擦来弥补操作过程中物理特性估计中的不准确性的见解。特别是，我们得出了在旋转操纵过程中摩擦提供的稳定性边缘的分析表达式。然后将此边距用于双光轨迹优化算法中，以设计最大化此稳定性余量的控制器，以提供对象物理特性中不确定性的鲁棒性。我们使用6 DOF操纵器来演示我们提出的方法来操纵几个不同的对象。
Generalizable manipulation requires that robots be able to interact with novel objects and environment. This requirement makes manipulation extremely challenging as a robot has to reason about complex frictional interaction with uncertainty in physical properties of the object. In this paper, we study robust optimization for control of pivoting manipulation in the presence of uncertainties. We present insights about how friction can be exploited to compensate for the inaccuracies in the estimates of the physical properties during manipulation. In particular, we derive analytical expressions for stability margin provided by friction during pivoting manipulation. This margin is then used in a bilevel trajectory optimization algorithm to design a controller that maximizes this stability margin to provide robustness against uncertainty in physical properties of the object. We demonstrate our proposed method using a 6 DoF manipulator for manipulating several different objects.
