Jiang Ping, Chiba Ryosuke, Takakusaki Kaoru, Ota Jun
Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Research Center for Brain Function and Medical Engineering, Asahikawa Medical University, Asahikawa, Japan.
PLoS One. 2016 Sep 21;11(9):e0163212. doi: 10.1371/journal.pone.0163212. eCollection 2016.
The development of a physiologically plausible computational model of a neural controller that can realize a human-like biped stance is important for a large number of potential applications, such as assisting device development and designing robotic control systems. In this paper, we develop a computational model of a neural controller that can maintain a musculoskeletal model in a standing position, while incorporating a 120-ms neurological time delay. Unlike previous studies that have used an inverted pendulum model, a musculoskeletal model with seven joints and 70 muscular-tendon actuators is adopted to represent the human anatomy. Our proposed neural controller is composed of both feed-forward and feedback controls. The feed-forward control corresponds to the constant activation input necessary for the musculoskeletal model to maintain a standing posture. This compensates for gravity and regulates stiffness. The developed neural controller model can replicate two salient features of the human biped stance: (1) physiologically plausible muscle activations for quiet standing; and (2) selection of a low active stiffness for low energy consumption.
开发一种生理上合理的神经控制器计算模型，该模型能够实现类人双足站立，这对于大量潜在应用非常重要，比如辅助设备开发和设计机器人控制系统。在本文中，我们开发了一种神经控制器计算模型，它可以在纳入120毫秒神经时延的情况下，使肌肉骨骼模型保持站立姿势。与以往使用倒立摆模型的研究不同，我们采用了一个具有七个关节和70个肌腱驱动装置的肌肉骨骼模型来表示人体解剖结构。我们提出的神经控制器由前馈控制和反馈控制组成。前馈控制对应于肌肉骨骼模型维持站立姿势所需的恒定激活输入。这可以补偿重力并调节刚度。所开发的神经控制器模型能够复制人类双足站立的两个显著特征：（1）安静站立时生理上合理的肌肉激活；（2）为降低能量消耗而选择低主动刚度。
