Modélisations et stratégie de prise pour la manipulation d'objets déformables

Abstract

Dexterous manipulation is an important issue in robotics research in which few works have tackled deformable object manipulation. New applications in surgery, food industry or in service robotics require mastering the grasping and manipulation of deformable objects. This thesis focuses on deformable object manipulation by anthropomorphic mechanical graspers such as multi-fingered articulated hands. This task requires a great expertise in mechanical modeling and control: interaction modeling, tactile and vision perception, force / position control of finger movements to ensure stable grasping. The work presented in this thesis focuses on modeling the grasping of deformable objects. To this end, we used a discretization by non-linear mass-spring systems to model deformable bodies in large displacements and deformations while having a low computational cost. To predict the interaction forces between robot hand and deformable object, we proposed an original approach based on a visco-elasto-plastic rheological model to evaluate tangential contact forces and describe the transition between the sticking and slipping modes. The contact forces are evaluated at nodes as function of the relative movements between the fingertips and the surface mesh facets of the manipulated object. Another contribution of this thesis is the use of this model in the planning of 3D deformable object manipulation tasks. This planning consists in determining the optimal configuration of the hand for grasping the objects as well as the paths to track and the efforts to be applied by the fingers to control the deformation of the object while ensuring the stability of the operation. The experimental validation of this work has been carried out on two robotic platforms: a Barrett hand embedded on a Adept S1700D ® manipulator and a Shadow hand embedded on a Kuka LWR4+® manipulator.