Case Western Reserve University, Cleveland, OH 44106, United States of America.
Bioinspir Biomim. 2017 Oct 16;12(6):065002. doi: 10.1088/1748-3190/aa8290.
A neuromechanical simulation of a planar, bipedal walking robot has been developed. It is constructed as a simplified, planar musculoskeletal model of the biomechanics of the human lower body. The controller consists of a dynamic neural network with central pattern generators (CPGs) entrained by force and movement sensory feedback to generate appropriate muscle forces for walking. The CPG model is a two-level architecture, which consists of separate rhythm generator and pattern formation networks. The biped model walks stably in the sagittal plane without inertial sensors or a centralized posture controller or a 'baby walker' to help overcome gravity. Its gait is similar to humans' and it walks at speeds from 0.850 m s up to 1.289 m s with leg length of 0.84 m. The model walks over small unknown steps (6% of leg length) and up and down 5° slopes without any additional higher level control actions.
已经开发出一种平面双足步行机器人的神经机械模拟。它是作为人体下肢生物力学的简化平面骨骼肌肉模型构建的。控制器由具有中央模式发生器 (CPG) 的动力神经网络组成，由力和运动感觉反馈来产生适当的肌肉力量来行走。CPG 模型是一个两级架构，它由单独的节律发生器和模式形成网络组成。双足模型在不使用惯性传感器或集中式姿势控制器或“婴儿助步车”的情况下在矢状面中稳定行走，以克服重力。它的步态类似于人类，速度从 0.850 米/秒到 1.289 米/秒，腿长为 0.84 米。该模型可以在不进行任何其他高级控制操作的情况下，在小的未知台阶（腿长的 6%）上行走，以及在 5°的斜坡上上下行走。
