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A Manipulation Control Strategy for Granular Materials Based on a Gaussian Mixture Model

Abstract : In the context of metal additive manufacturing, one of the most attractive tasks to be robotized is the cleaning process of metal powder after the printing operations. This task presents a challenging scenario for most of robot manipulation approaches in the literature. In this paper we present an approach, marker-less and real time affordable , which address the cleaning problem like a shape manipulation control problem. This control strategy is designed as an optimization problem. The error function is written as a lagrangian function using an objective function based on Gaussian Mixture Model (GMM). The local optimization is performed by a gradient descent and a global optimization process is used to avoid local minima.
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https://hal.uca.fr/hal-02379943
Contributor : Juan Antonio Corrales Ramon <>
Submitted on : Monday, November 25, 2019 - 11:45:47 PM
Last modification on : Thursday, March 5, 2020 - 3:29:38 PM
Long-term archiving on: : Wednesday, February 26, 2020 - 10:21:04 PM

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Carlos Mateo, Juan Antonio Corrales Ramon, Youcef Mezouar. A Manipulation Control Strategy for Granular Materials Based on a Gaussian Mixture Model. Conference Proceedings of "Robot 2019: Fourth Iberian Robotics Conference", Springer, pp.171-183, 2020, 978-3-030-36149-5. ⟨10.1007/978-3-030-36150-1_15⟩. ⟨hal-02379943⟩

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