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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.
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https://hal-cea.archives-ouvertes.fr/cea-03387866
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Submitted on : Thursday, November 4, 2021 - 5:36:49 PM
Last modification on : Thursday, February 17, 2022 - 10:08:04 AM
Long-term archiving on: : Saturday, February 5, 2022 - 7:29:49 PM

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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⟩

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