Human initiated grasp space exploration algorithm for an underactuated robot gripper using variational autoencoder - CEA - Commissariat à l’énergie atomique et aux énergies alternatives Access content directly
Conference Papers Year : 2021

Human initiated grasp space exploration algorithm for an underactuated robot gripper using variational autoencoder

Abstract

Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents an efficient procedure for exploring the grasp space of a multifingered adaptive gripper for generating reliable grasps given a known object pose. This procedure relies on a limited dataset of manually specified expert grasps, and use a mixed analytic and data-driven approach based on the use of a grasp quality metric and variational autoencoders. The performances of this method are assessed by generating grasps in simulation for three different objects. On this grasp planning task, this method reaches a grasp success rate of 99.91% on 7000 trials.
Fichier principal
Vignette du fichier
article_icra.pdf (3.01 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Licence : Copyright

Dates and versions

cea-03387866 , version 1 (04-11-2021)

Identifiers

Cite

Clement Rolinat, Mathieu Grossard, Saifeddine Aloui, Christelle Godin. Human initiated grasp space exploration algorithm for an underactuated robot gripper using variational autoencoder. ICRA 2021 - International Conference on Robotics and Automation, May 2021, Xi'an, China. pp.2598-2604, ⟨10.1109/ICRA48506.2021.9561765⟩. ⟨cea-03387866⟩
68 View
66 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More