论文标题
对复杂人类运动行为的研究：从爬行到行走
The Study of Complex Human Locomotion Behaviors: From Crawling to Walking
论文作者
论文摘要
本文使用简单的状态机来开发一种控制算法，以在简单的模型系统的背景下控制婴儿类人。该算法的灵感来自一个婴儿，他开始学习在7至12个月大时才站立并行走：他或她最初学习爬行，然后，一旦下肢肌肉足够强大，就可以通过支撑他或她的上层后备箱来学习走路。理想情况下，这种算法支持的运动可以将婴儿带到任何期望的位置：一堆玩具，美味的小吃或婴儿的父母或亲戚。在本文中，我们分析了爬行阶段，简单的2D两足体模型以及8到18个月大的初始步行形式，并定量评估这些阶段的理想运动学模型和仿真结果。
This paper uses a simple state machine to develop a control algorithm for controlling an infant humanoid in the context of a simple model system. The algorithm is inspired by a baby who starts learning to stand and walk at 7 to 12 months of age: he or she initially learns to crawl and then, once the lower limb muscles are strong enough, can learn to walk by coming to support his or her upper trunk. Ideally, this algorithm-supported locomotion can take the baby to any desired location: a pile of toys, a tasty snack, or the baby's parents or relatives. In this paper we analyze the crawling stage, the simple 2d bipedal model, and the initial walking form from 8 to 18 months of age, and quantitatively evaluate the ideal kinematics model and simulation results for these stages.
