no code implementations • 10 Mar 2024 • Johann Huber, François Hélénon, Mathilde Kappel, Elie Chelly, Mahdi Khoramshahi, Faïz Ben Amar, Stéphane Doncieux
We believe these results to be a significant step toward the generation of large datasets that can lead to robust and generalizing robotic grasping policies.
1 code implementation • 6 Oct 2023 • Johann Huber, François Hélénon, Hippolyte Watrelot, Faiz Ben Amar, Stéphane Doncieux
More than 7000 reach-and-grasp trajectories have been generated with Quality-Diversity (QD) methods on 3 different arms and grippers, including parallel fingers and a dexterous hand, and tested in the real world.
1 code implementation • 6 Oct 2023 • François Hélénon, Johann Huber, Faïz Ben Amar, Stéphane Doncieux
This framework addresses two main issues: the lack of an off-the-shelf vision module for detecting object pose and the generalization of QD trajectories to the whole robot operational space.
no code implementations • 14 Oct 2022 • Johann Huber, Oumar Sane, Alex Coninx, Faiz Ben Amar, Stephane Doncieux
Robotics grasping refers to the task of making a robotic system pick an object by applying forces and torques on its surface.