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Recent Developments on Modeling for a 3-DOF Micro-Hand Based on AI Methods

机译:基于AI方法的三-TOF微手建模的最新发展

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摘要

Recently, soft actuators have been expected to have many applications in various fields. Most of the actuators are composed of flexible materials and driven by air pressure. The 3-DOF micro-hand, which is a kind of soft actuator, can realize a three degrees of freedom motion by changing the applied air pressure pattern. However, the input–output relation is nonlinear and complicated. In previous research, a model of the micro-hand was proposed, but an error between the model and the experimental results was large. In this paper, modeling for the micro-hand is proposed by using multi-output support vector regression (MSVR) and ant colony optimization (ACO), which is one of the artificial intelligence (AI) methods. MSVR estimates the input–output relation of the micro-hand. ACO optimizes the parameters of the MSVR model.
机译:最近,预计软致执行器将在各种领域中具有许多应用。大多数致动器由柔性材料构成,并由空气压力驱动。作为一种软致动器的3-DOF微手,可以通过改变施加的空气压力模式来实现三个自由度运动。但是,输入输出关系是非线性和复杂的。在以前的研究中,提出了一种微手模型,但模型与实验结果之间的误差很大。在本文中,通过使用多输出支持向量回归(MSVR)和蚁群优化(ACO)来提出用于微手的建模,这是人工智能(AI)方法之一。 MSVR估计微手的输入输出关系。 ACO优化MSVR模型的参数。

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