论文标题
可视觉动作计划的潜在空间路线图，可变形和刚性对象操纵
Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation
论文作者
论文摘要
我们提出了一个具有高维状态空间（例如操纵可变形物体）的复杂操纵任务的视觉动作计划的框架。计划在嵌入图像的低维潜在空间中执行。我们定义并实施了潜在的空间路线图（LSR），该路线图是一个基于图形的结构，可在全球范围内捕获潜在系统动力学。我们的框架由两个主要组成部分组成：一个视觉概要模块（VFM），该模块（VFM）将视觉计划作为一系列图像序列以及一个预测它们之间的动作的动作提案网络（APN）。我们在模拟的盒子堆叠任务以及使用真实机器人执行的T恤折叠任务上显示了该方法的有效性。
We present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces such as manipulation of deformable objects. Planning is performed in a low-dimensional latent state space that embeds images. We define and implement a Latent Space Roadmap (LSR) which is a graph-based structure that globally captures the latent system dynamics. Our framework consists of two main components: a Visual Foresight Module (VFM) that generates a visual plan as a sequence of images, and an Action Proposal Network (APN) that predicts the actions between them. We show the effectiveness of the method on a simulated box stacking task as well as a T-shirt folding task performed with a real robot.
