附肢协调中的随机性有助于 strenuous 地面自扶正
Randomness in appendage coordination facilitates strenuous ground self-righting
AI总结：
本文通过蟑螂启发的机器人仿真研究，证明在翼-腿协调中引入随机性有助于系统摆脱不利亚稳态、探索更多相位，从而显著提高 strenuous 地面自扶正的成功率。
摘要：
随机性在生物和人工系统中普遍存在，其来源既可能是环境的随机性，也可能是生物体或设备自身的噪声。在运动控制中，随机性通常被视为一种干扰。例如，在动态行走过程中，随机地形中的随机性会导致亚稳态动力学，必须加以抑制才能使系统稳定在极限环附近。本文研究了运动中的随机性是否对 strenuous 运动任务有益。我们的研究使用了机器人仿真模型，模拟在蟑螂中观察到的 strenuous、腿辅助、带翼的地面自扶正行为，该行为中存在异常大的翅膀和腿部运动随机性。我们开发了一个简化的仿真机器人，能够产生类似的自扶正行为，并改变翼-腿协调中的随机性水平。在每次翅膀打开尝试中，翅膀打开与腿摆动之间的时间延迟中加入的随机性越多，naive 机器人（不知道何种协调最优）在有限时间内实现自扶正的可能性就越大。以翅膀和腿部振荡之间的相位衡量的翼-腿协调对自扶正结果具有关键影响。在没有随机性的情况下，周期性的翅膀和腿部振荡往往使系统只访问少数几个不利相位，导致无法从亚稳态中逃逸。加入随机性后，系统能够充分探索各个相位，并有更大机会遇到有利于自扶正的相位。我们的研究补充了先前的工作，证明随机性有助于使运动系统摆脱被束缚在不利亚稳态中的困境，而这种情况在 strenuous 运动中很常见。
英文摘要：
Randomness is common in biological and artificial systems, resulting either from stochasticity of the environment or noise in organisms or devices themselves. In locomotor control, randomness is typically considered a nuisance. For example, during dynamic walking, randomness in stochastic terrain leads to metastable dynamics, which must be mitigated to stabilize the system around limit cycles. Here, we studied whether randomness in motion is beneficial for strenuous locomotor tasks. Our study used robotic simulation modeling of strenuous, leg-assisted, winged ground self-righting observed in cockroaches, in which unusually large randomness in wing and leg motions is present. We developed a simplified simulation robot capable of generating similar self-righting behavior and varied the randomness level in wing-leg coordination. During each wing opening attempt, the more randomness added to the time delay between wing opening and leg swinging, the more likely it was for the naive robot (which did not know what coordination is best) to self-right within a finite time. Wing-leg coordination, measured by the phase between wing and leg oscillations, had a crucial impact on self-righting outcome. Without randomness, periodic wing and leg oscillations often limited the system to visit a few bad phases, leading to failure to escape from the metastable state. With randomness, the system explored phases thoroughly and had a better chance of encountering good phases to self-right. Our study complements previous work by demonstrating that randomness helps destabilize locomotor systems from being trapped in undesired metastable states, a situation common in strenuous locomotion.
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