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Statistical modeling and design issues of a crossbeam sensor

机译:横梁传感器的统计建模和设计问题

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摘要

The basic idea of RISC (reduced intricacy sensing and control) robotics is an attempt to perform challenging industrial manufacturing tasks by using a combination of simple hardware and sophisticated algorithms. Many effective strategies and algorithms have been explored. However, the issue of optimal design of RISC sensor has not been solved. The main reason is the shortage of good models. In this paper, we propose a statistical model for one of the typical RISC sensors, i.e. the crossbeam sensor. Based on this statistical model we employ the multiple hypotheses-testing method as optimal design technique and present its applied strategies. It is believed that this work will lead to development of new RISC sensors because a new principle and a pertinent model are introduced into this area.
机译:RISC(减少复杂性检测和控制)机器人技术的基本思想是尝试通过结合使用简单的硬件和复杂的算法来执行具有挑战性的工业制造任务。已经探索了许多有效的策略和算法。但是,RISC传感器的优化设计问题尚未解决。主要原因是缺乏好的模型。在本文中,我们为一种典型的RISC传感器(即横梁传感器)提出了一种统计模型。基于此统计模型,我们采用多重假设检验方法作为最佳设计技术,并提出其应用策略。相信这项工作将导致新的RISC传感器的开发,因为在该领域引入了新的原理和相关的模型。

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