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A soft sensor for the estimation of ionic electroactive actuator motion based on deep learning

Bruno Andò, Salvatore Graziani, Maria Gabriella Xibilia

发表年份
2018
引用次数
3

摘要

In this paper, a black-box model, suitable for being used as a Soft Sensor for an Ionic Polymer-Metal Composite, is introduced. Applications of such materials, in many fields, such as bio-inspired robotics, medicine, and aerospace, have been reported. The proposed Soft Sensor is a data-driven Nonlinear Finite Impulse Response model, implemented by using a Deep Neural Network, where the output is estimated only on the basis of input past samples. The model has been selected with the aim of eliminating any hardware position sensor and, therefore, reducing the complexity of the positioning system.

关键词

Soft sensorActuatorSoft roboticsComputer scienceArtificial intelligenceAerospaceArtificial neural networkNonlinear systemImpulse (physics)Robotics

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