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Pré-Publication, Document De Travail Année : 2020

Vision-based Manipulation of Deformable and Rigid Objects Using Subspace Projections of 2D Contours

Jihong Zhu
Robin Passama
Andrea Cherubini

Résumé

This paper proposes a unified vision-based manipulation framework using image contours of deformable/rigid objects. Instead of using human-defined cues, the robot automatically learns the features from processed vision data. Our method simultaneously generates-from the same data-both, visual features and the interaction matrix that relates them to the robot control inputs. Extraction of the feature vector and control commands is done online and adaptively, with little data for initialization. The method allows the robot to manipulate an object without knowing whether it is rigid or deformable. To validate our approach, we conduct numerical simulations and experiments with both deformable and rigid objects.
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Dates et versions

hal-02558064 , version 1 (29-04-2020)
hal-02558064 , version 2 (21-08-2020)
hal-02558064 , version 3 (22-04-2021)

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  • HAL Id : hal-02558064 , version 1

Citer

Jihong Zhu, David Navarro-Alarcon, Robin Passama, Andrea Cherubini. Vision-based Manipulation of Deformable and Rigid Objects Using Subspace Projections of 2D Contours. 2020. ⟨hal-02558064v1⟩
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