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寻找节奏:人类在周期性交互任务中利用顺应系统的非线性固有动力学。

Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks.

机构信息

Sensor Based Robotic Systems and Intelligent Assistance Systems, TUM School of Computation, Information and Technology, Technical University of Munich (TUM), Garching, Germany.

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Wessling, Germany.

出版信息

PLoS Comput Biol. 2024 Sep 3;20(9):e1011478. doi: 10.1371/journal.pcbi.1011478. eCollection 2024 Sep.

Abstract

Activities like ball bouncing and trampoline jumping showcase the human ability to intuitively tune to system dynamics and excite motions that the system prefers intrinsically. This human sensitivity to resonance has been experimentally supported for interactions with simple linear systems but remains a challenge to validate in more complex scenarios where nonlinear dynamics cannot be predicted analytically. However, it has been found that many nonlinear systems exhibit periodic orbits similar to the eigenmodes of linear systems. These nonlinear normal modes (NNM) are computable with a recently developed numerical mode tool. Using this tool, the present resarch compared the motions that humans excite in nonlinear systems with the predicted NNM of the energy-conservative systems. In a user study consisting of three experiment parts, participants commanded differently configured virtual double pendula with joint compliance through a haptic joystick. The task was to alternately hit two targets, which were either aligned with the NNM (Experiments 1 and 2) or purposefully arranged offset (Experiment 3). In all tested experiment variations, participants intuitively applied a control strategy that excited the resonance and stabilized an orbit close to the ideal NNM of the conservative systems. Even for increased task accuracy (Experiment 2) and targets located away from the NNM (Experiment 3), participants could successfully accomplish the task, likely by adjusting their arm stiffness to alter the system dynamics to better align the resonant motions to the task. Consequently, our experiments extend the existing research on human resonance sensitivity with data-based evidence to nonlinear systems. Our findings emphasize the human capabilities to apply control strategies to excite and exploit resonant motions in dynamic object interactions, including possibly shaping the dynamics through changes in muscle stiffness.

摘要

弹跳球和蹦床跳跃等活动展示了人类能够直观地调整系统动力学并激发系统内在偏好的运动。人类对共振的敏感性已经在与简单线性系统的相互作用中得到了实验支持,但在更复杂的情况下,非线性动力学无法进行分析预测,这仍然是一个挑战。然而,人们已经发现,许多非线性系统表现出类似于线性系统本征模式的周期性轨道。这些非线性本征模式(NNM)可以使用最近开发的数值模式工具进行计算。利用该工具,本研究将人类在非线性系统中激发的运动与能量守恒系统的预测 NNM 进行了比较。在一个由三个实验部分组成的用户研究中,参与者通过触觉操纵杆指挥具有关节顺应性的不同配置的虚拟双摆。任务是交替击打两个目标,这些目标要么与 NNM 对齐(实验 1 和 2),要么故意偏离(实验 3)。在所有测试的实验变化中,参与者直观地应用了一种控制策略,该策略激发了共振并稳定了一个接近保守系统理想 NNM 的轨道。即使任务精度增加(实验 2)且目标远离 NNM(实验 3),参与者也能够成功完成任务,可能是通过调整手臂刚度来改变系统动力学,以更好地将共振运动与任务对齐。因此,我们的实验通过基于数据的证据将人类共振敏感性的现有研究扩展到了非线性系统。我们的研究结果强调了人类应用控制策略激发和利用动态物体相互作用中共振运动的能力,包括可能通过改变肌肉刚度来塑造动力学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7c3/11398697/a529228eabfa/pcbi.1011478.g002.jpg

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