研究新手操作者在远程操控中的动态特性，助力提升系统稳定性与效率。
Linearity, Time Invariance, and Passivity of a Novice Person in Human Teleoperation
- 通过建模与实验验证操作者近似线性时不变，耦合弱且具强被动性。
- 在实际频率下，操作者系统被动性显著过剩，利于稳定控制。
- 适用于医疗远程操作等需高精度人机协作的场景。
低成本的医疗程序远程指导对偏远和资源匮乏地区医疗可及性至关重要。人机遥操作是一种新方法，可通过混合现实（MR）界面让新手以较高精度和效率完成操作。已有研究表明，新手（即跟随者）能可靠追踪MR输入，性能接近遥控机器人系统。因此，理解并控制跟随者的动态特性对优化系统性能、实现稳定透明的双向遥操作至关重要。线性、时不变性、轴间耦合和被动性是遥操作与控制器设计中的关键因素。本文探讨了这些特性在人类跟随者中的表现。实验与建模表明，跟随者可近似视为线性时不变系统，耦合极小，且在实用频率下具有显著的被动性冗余。此外，本文推导出跟随者动态的随机模型。这些结果将有助于控制器设计与分析，从而提升人机遥操作性能。
原文摘要 · Abstract (English)
Low-cost teleguidance of medical procedures is becoming essential to provide healthcare to remote and underserved communities. Human teleoperation is a promising new method for guiding a novice person with relatively high precision and efficiency through a mixed reality (MR) interface. Prior work has shown that the novice, or "follower", can reliably track the MR input with performance not unlike a telerobotic system. As a consequence, it is of interest to understand and control the follower's dynamics to optimize the system performance and permit stable and transparent bilateral teleoperation. To this end, linearity, time-invariance, inter-axis coupling, and passivity are important in teleoperation and controller design. This paper therefore explores these effects with regard to the follower person in human teleoperation. It is demonstrated through modeling and experiments that the follower can indeed be treated as approximately linear and time invariant, with little coupling and a large excess of passivity at practical frequencies. Furthermore, a stochastic model of the follower dynamics is derived. These results will permit controller design and analysis to improve the performance of human teleoperation.
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