PrendoSim: proxy-hand-based robot grasp generator

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

  • Diar Abdlkarim
  • Tommaso Pardi
  • Katherine J Kuchenbecker

Colleges, School and Institutes

Abstract

The synthesis of realistic robot grasps in a simulated environment is pivotal in generating datasets that support sim-to-real transfer learning. In a step toward achieving this goal, we propose PrendoSim, an open-source grasp generator based on a proxy-hand simulation that employs NVIDIA’s physics engine (PhysX) and the recently released articulated-body objects developed by Unity (https://prendosim.github.io). We present the implementation details, the method used to generate grasps, the approach to operationally evaluate stability of the generated grasps, and examples of grasps obtained with two different grippers (a parallel jaw gripper and a three-finger hand) grasping three objects selected from the YCB dataset (hammer, screwdriver, and scissors). Compared to simulators proposed in the literature, PrendoSim balances grasp realism and ease of use, displaying an intuitive interface and enabling the user to produce a large and varied dataset of stable grasps.

Details

Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Informatics in Control, Automation and Robotics
EditorsOleg Gusikhin, Henk Nijmeijer, Kurosh Madani
Publication statusPublished - 2021
Event18th International Conference on Informatics in Control, Automation and Robotics - Online
Duration: 6 Jul 20218 Jul 2021
http://www.icinco.org/

Conference

Conference18th International Conference on Informatics in Control, Automation and Robotics
Abbreviated titleICINCO 2021
Period6/07/218/07/21
Internet address