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Conference Papers Year : 2020

Simultaneous Tracking and Elasticity Parameter Estimation of Deformable Objects


In this paper, we propose a novel method to simultaneously track the deformation of soft objects and estimate their elasticity parameters. The tracking of the deformable object is performed by combining the visual information captured by a RGB-D sensor with interactive Finite Element Method simulations of the object. The visual information is more particularly used to distort the simulated object. In parallel, the elasticity parameter estimation minimizes the error between the tracked object and a simulated object deformed by the forces that are measured using a force sensor. Once the elasticity parameters are estimated, our tracking algorithm can be used to estimate the deformation forces applied to an object without the use of a force sensor. We validated our method on several soft objects with different shape complexities. Our evaluations show the ability of our method to estimate the elasticity parameters as well as its use to estimate the forces applied to a deformable object without any force sensor. These results open novel perspectives to better track and control deformable objects during robotic manipulations.
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Dates and versions

hal-02495831 , version 1 (02-03-2020)
hal-02495831 , version 2 (04-05-2020)


  • HAL Id : hal-02495831 , version 2


Agniva Sengupta, Romain Lagneau, Alexandre Krupa, Eric Marchand, Maud Marchal. Simultaneous Tracking and Elasticity Parameter Estimation of Deformable Objects. ICRA 2020 - IEEE International Conference on Robotics and Automation, May 2020, Paris, France. pp.1-7. ⟨hal-02495831v2⟩
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