论文标题
基于干扰预测控制的可转移的腿部移动操纵框架
A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control
论文作者
论文摘要
由于它们适应不同地形的能力，四倍的机器人在机器人学习的研究领域引起了很多关注。四足机器人配备了机器人臂的腿部移动操作可以极大地提高机器人在各种操纵任务中的性能。从控制理论的角度来看，几项先前的工作已经调查了腿部移动操作。但是，为各种机器人臂和四倍的机器人建模统一结构是一项艰巨的任务。在本文中，我们提出了一个统一的框架干扰预测控制，其中使用潜在动态适配器的增强学习方案嵌入了我们提出的低级控制器中。我们的方法可以很好地适应各种类型的机器人臂，并提供一些随机运动样品，实验结果证明了我们方法的有效性。
Due to their ability to adapt to different terrains, quadruped robots have drawn much attention in the research field of robot learning. Legged mobile manipulation, where a quadruped robot is equipped with a robotic arm, can greatly enhance the performance of the robot in diverse manipulation tasks. Several prior works have investigated legged mobile manipulation from the viewpoint of control theory. However, modeling a unified structure for various robotic arms and quadruped robots is a challenging task. In this paper, we propose a unified framework disturbance predictive control where a reinforcement learning scheme with a latent dynamic adapter is embedded into our proposed low-level controller. Our method can adapt well to various types of robotic arms with a few random motion samples and the experimental results demonstrate the effectiveness of our method.
