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.
CITATION STYLE
Mateo, C. M., Corrales, J. A., & Mezouar, Y. (2020). A Manipulation Control Strategy for Granular Materials Based on a Gaussian Mixture Model. In Advances in Intelligent Systems and Computing (Vol. 1093 AISC, pp. 171–183). Springer. https://doi.org/10.1007/978-3-030-36150-1_15
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