Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
复制标题
刚体协同操纵的分散自适应控制
DOI：
10.1109/tro.2021.3072021
复制
发表时间：
2020
影响因子：
7.8
通讯作者：
M. Schwager
中科院分区：
文献类型：
--
作者：
Preston Culbertson;J. Slotine;M. Schwager
在这项工作中，我们考虑一组机器人一起工作来操纵刚性物体来跟踪 $\text{SE}(3)$ 中的所需轨迹。机器人不知道物体的质量或摩擦特性，也不知道它们附着在物体上的位置。然而，他们可以通过一个机器人向团队广播其测量值，或者通过所有机器人通信并平均其状态测量值来估计其质心状态，从而访问通用状态测量值。为了解决这个问题，我们提出了一种分散自适应控制方案，其中每个代理维护并调整自己对对象参数的估计，以跟踪参考轨迹。我们对控制器的行为进行了分析，并表明所有闭环信号都保持有界，并且系统轨迹几乎总是（除了一组测量零的初始条件）收敛到所需轨迹。我们使用 3D 操纵任务的数值模拟以及在平面操纵任务上演示我们的算法的硬件实验来研究所提出的控制器的性能。这些研究综合起来证明了所提出的控制器的有效性，即使存在大量未建模的效应，例如离散化误差和复杂的摩擦相互作用。
In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $\text{SE}(3)$. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller’s behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller’s performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions.