BURG-toolkit: robot grasping experiments in simulation and the real world

Martin Rudorfer, Markus Suchi, Mohan Sridharan, Markus Vincze, Ales Leonardis

Research output: Contribution to conferencePaperpeer-review

Abstract / Description of output

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/
Original languageEnglish
Publication statusPublished - 27 May 2022
Event39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States
Duration: 23 May 202227 May 2022

Conference

Conference39th IEEE International Conference on Robotics and Automation, ICRA 2022
Country/TerritoryUnited States
CityPhiladelphia
Period23/05/2227/05/22

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