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The Robot Selection Problem for Mini-Parallel Kinematic Machines: A Task-Driven Approach to the Selection Attributes Identification

机译:迷你平行运动机器的机器人选择问题:选择属性识别的任务驱动方法

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摘要

In the last decades, the Robot Selection Problem (RSP) has been widely investigated, and the importance of properly structuring the decision problem has been stated. Crucial aspect in this process is the correct identification of the robot attributes, which should be limited in number as much as possible, but should be also able to detect at best the peculiar requirements of specific applications. Literature describes several attributes examples, but mainly dedicated to traditional industrial tasks, and applied to the selection of conventional industrial robots. After a synthetic review of the robot attributes depicted in the RSP literature, presented with a custom taxonomy, this paper proposes a set of possible requirements for the selection problem of small scale parallel kinematic machines (PKMs). The RSP is based on a task-driven approach: two mini-manipulators are compared as equivalent linear actuators to be integrated within a more complex system, for the application in both an industrial and a biomedical environment. The set of identified criteria for the two environments is proposed in the results and investigated with respect to working conditions and context in the discussion, emphasizing limits and strength points of this approach; finally, the conclusions synthesizes the main results.
机译:在过去的几十年中,机器人选择问题(RSP)已被广泛调查,并陈述了正确构建决策问题的重要性。该过程中的重要方面是机器人属性的正确识别,其应该尽可能地限制,但也应该能够以最佳的特定应用程序检测。文献描述了几个属性示例,但主要致力于传统的工业任务,并应用于常规工业机器人的选择。在RSP文献中描绘的机器人属性的合成审查之后,本文提出了一系列可能对小规模平行运动机器(PKMS)的选择问题的要求。 RSP基于任务驱动的方法:将两个迷你操纵器与等同的线性执行器进行比较,以集成在更复杂的系统内,用于工业和生物医学环境中的应用。在结果中提出了这两个环境的确定标准,并在讨论中对工作条件和背景进行了调查,强调这种方法的限制和强度点;最后,结论综合了主要结果。

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