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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >A Modular Mechatronic Device for Arm Stiffness Estimation in Human–Robot Interaction
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A Modular Mechatronic Device for Arm Stiffness Estimation in Human–Robot Interaction

机译:用于人机交互中手臂刚度估算的模块化机电一体化装置

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摘要

Measuring human arm stiffness in robot interaction is a crucial topic in both neuroscience and the related learning process during skill acquisition and functional recovery in neurological subjects. However, it is a complex and time-consuming procedure often requiring a computational burden which prevents from an online estimation of the data. Most systems described in the previous literature uses robotic manipulandum to estimate limb stiffness by perturbing the arm across different directions over multiple trials and acquiring the corresponding restoring forces. The proposed method is still robust and accurate, although with rather strong limitations in terms of speed and acquisition bandwidth. For this reason, we designed a mechatronic device able to carry out endpoint stiffness estimation within in a single trial. The proposed system can be operated in a stand-alone configuration or can be plugged in a robotic manipulandum, allowing us to perform the measurement during a posture maintaining task in contact with the robotic counterpart. This paper describes the mechanism and the design, testing the device in different experimental contexts, using a customized test bench to characterize the potentials and the limits of the proposed architecture. Furthermore, we tested the system on human subjects to obtain a reliable bidimensional estimation of arm stiffness when it is plugged in a robotic device. Results are reported and discussed in detail highlighting the limitations and the advantages of using the proposed solution.
机译:在机器人学中,测量人手臂的僵硬度是神经科学和相关学习过程中神经科学科目的技能获取和功能恢复中的重要课题。但是,这是一个复杂且耗时的过程,通常需要一定的计算负担,这会阻止在线估计数据。先前文献中描述的大多数系统都使用机械手manmanpulandum通过多次试验在不同方向上扰动手臂并获得相应的恢复力来估计肢体僵硬。尽管在速度和采集带宽方面有相当大的局限性,但所提出的方法仍然健壮且准确。因此,我们设计了一种机电一体化设备,能够在一次试验中进行端点刚度估算。所提出的系统可以以独立配置进行操作,也可以插入机器人手掌中,从而使我们能够在与机器人手接触的姿势保持任务中执行测量。本文介绍了这种机制和设计,并在不同的实验环境下对设备进行了测试,使用定制的测试台来表征所提出架构的潜力和局限性。此外,我们在人体对象上测试了该系统,以便在将其插入机器人设备中时获得可靠的手臂刚度二维估算。报告并详细讨论了结果,突出了使用提出的解决方案的局限性和优势。

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