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24/05/19 : Soutenance de thèse de Jose SANCHEZ LOZA

Le Vendredi 24 Mai à 10h00, Monsieur Jose Sanchez Loza soutiendra publiquement sa thèse de doctorat intitulée:

"Shape Sensing of Deformable Objects for Robot Manipulation"

Lieu: Amphi Recherche - EUPI, Campus des Cézeaux, 63170 AUBIERE

 

Ces travaux ont été réalisés dans l'équipe Maccs de l'axe ISPR de l'Institut Pascal, sous la direction de :

- Youcef Mezouar, Professeur (directeur de thèse)
- Juan Antonio Corrales Ramon, Maître de conférences (encadrant)
- Chedli Bouzgarrou, Maître de conférences (encadrant)

RESUMÉ

Deformable objects are ubiquitous in our daily lives. On a given day, we manipulate clothes into uncountable con gurations to dress ourselves, tie the shoelaces on our shoes, pick up fruits and vegetables without damaging them for our consumption and fold receipts into our wallets. All these tasks involve manipulating deformable objects and can be performed by an able person without any trouble, however robots have yet to reach the same level of dexterity. Unlike rigid objects, where robots are now capable of handling objects with close to human performance in some tasks; deformable objects must be controlled not only to account for their pose but also their shape. This extra constraint, to control an object's shape, renders techniques used for rigid objects mainly innapplicable to deformable objects. Furthermore, the behavior of deformable objects widely di ers among them, e.g. the shape of a cable and clothes are signi cantly a ected by gravity while it might not a ect the con guration of other deformable objects such as food products. Thus, di erent approaches have been designed for speci c classes of deformable objects.

In this thesis we seek to address these shortcomings by proposing a modular approach to sense the shape of an object while it is manipulated by a robot. The modularity of the approach is inspired by a programming paradigm that has been increasingly been applied to software development in robotics and aims to achieve more general solutions by separating functionalities into components. These components can then be interchanged based on the speci c task or object at hand. Our approach, thus, takes the form of a pipeline to sense the shape of deformable objects.

To validate the proposed pipeline, we implemented three di erent applications. Two applications focused exclusively on estimating the object's deformation using either tactile or force data, and the third application consisted in controlling the deformation of an object. An evaluation of the pipeline, performed on a set of elastic objects for all three applications, shows promising results for an approach that makes no use of visual information and hence, it could greatly be improved by the addition of this modality.