Fujii Keisuke, Yoshihara Yuki, Tanabe Hiroko, Yamamoto Yuji
Structured Learning Team, Center for Advanced Intelligence Project, Institute of Physical and Chemical Research (RIKEN)Suita, Japan.
Intelligence Mobility Group, Institutes of Innovation for Future Society, Nagoya UniversityNagoya, Japan.
Front Hum Neurosci. 2017 Jun 7;11:298. doi: 10.3389/fnhum.2017.00298. eCollection 2017.
Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.
人类能够通过协调冗余组件来适应突然变化的情况，即使是在两足运动中也是如此。传统的适应性已经通过各种计算方法得以再现，如最优控制、神经振荡器和强化学习；然而，由于动态不稳定的多连杆闭环系统，生物和社会活动所需的两足运动中的适应性，如追逐和逃避中不可预测的方向变化，仍是未知的。在此，我们提出一种切换适应模型，通过改进自主分布式控制来执行两足运动，其中自主执行器在无中央控制的情况下相互作用，并切换推进、平衡和腿部摆动的角色。我们的切换移动性模型仅使用三个执行器就能随时实现方向改变，尽管与无方向改变的可比模型相比，它显示出更高的运动成本。我们随时评估这种适应性的方法应作为理解通用运动控制的先决条件加以利用。所提出的算法可能简单地解释和预测人类两足运动中的适应机制，以协调肢体内部和之间的执行器功能。
