论文标题
Burg-Toolkit：在模拟和现实世界中的机器人抓住实验
BURG-Toolkit: Robot Grasping Experiments in Simulation and the Real World
论文作者
论文摘要
本文介绍了Burg-toolkit，这是一套开源工具，用于基准和理解机器人握把。我们的工具允许研究人员：（1）创建用于生成训练数据并在模拟中执行抓地力的虚拟场景； （2）通过在物理世界中准确地安排相应的对象进行真实的机器人实验来重新创建场景，从而支持对SIM到真实差距的分析； （3）与其他研究人员分享场景，以促进实验结果的可比性和可重复性。我们通过描述一些潜在用例来解释如何使用工具。我们进一步提供了概念验证实验结果，以量化某些示例场景中机器人抓住的SIM到真实差距。这些工具可在以下网址找到：https：//mrudorfer.github.io/burg-toolkit/
This paper presents BURG-Toolkit, a set of open-source tools for Benchmarking and Understanding Robotic Grasping. Our tools allow researchers to: (1) create virtual scenes for generating training data and performing grasping in simulation; (2) recreate the scene by arranging the corresponding objects accurately in the physical world for real robot experiments, supporting an analysis of the sim-to-real gap; and (3) share the scenes with other researchers to foster comparability and reproducibility of experimental results. We explain how to use our tools by describing some potential use cases. We further provide proof-of-concept experimental results quantifying the sim-to-real gap for robot grasping in some example scenes. The tools are available at: https://mrudorfer.github.io/burg-toolkit/
