关于装载适应性神经模糊系统的有两足行走的机器人的零刻点弹道造

关于装载适应性神经模糊系统的有两足行走的机器人的零刻点弹道造型(中文6000字,英文2600字)
D. Kim, S.-J. Seo and G.-T. Park
摘要：对于制造机器人来说两足动物的体系结构高度适用于它们工作在人的环境里，因为这样将使机器人避免障碍变成一项相对的容易的任务。 然而，在走动的机制中介入复杂动力学，这使得制作这样的机器人的控制系统变成了一项富有挑战性的任务。 机器人脚部的零刻点(ZMP)弹道是机器人行走时的稳定性的重要保障。 如果ZMP可以在线测量那么就将使为机器人稳定行走创造条件成为可能，而且通过运用标准的ZMP还可以实现机器人的稳定控制。ZMP数据是通过两足行走机器人实时测量出来的，在这之后在通过一套适应性神经模糊系统（ANFS）将其造型。测量了在水平基准面的自然行走和在带有10度倾斜面的上下行走。通过改变模糊系统的成员作用和结果输出部分的规则，使得ANFS造型的表现最优化。由ANFS展示的优秀表现意味着它不仅可以运用于模型机器人的运动，还可以运用于控制真正的机器人。

Zero-moment point trajectory modeling of a biped
walking robot using an adaptive neuro-fuzzy system
D. Kim, S.-J. Seo and G.-T. Park
Abstract: A bipedal architecture is highly suitable for a robot built to work in human environments [资料来源：https://www.doc163.com]
since such a robot will find avoiding obstacles a relatively easy task. However, the complex dynamics involved in the walking mechanism make the control of such a robot a challenging task.
The zero-moment point (ZMP) trajectory in the robot’s foot is a significant criterion for the robot’s
stability during walking. If the ZMP could be measured on-line then it becomes possible to create
stable walking conditions for the robot and here also stably control the robot by using the measured ZMP, values. ZMP data is measured in real-time situations using a biped walking robot and this ZMP data is then modelled using an adaptive neuro-fuzzy system (ANFS). Natural walking motions on flat level surfaces and up and down a 10° slope are measured. The modelling
performance of the ANFS is optimized by changing the membership functions and the consequent
part of the fuzzy rules. The excellent performance demonstrated by the ANFS means that it can not only be used to model robot movements but also to control actual robots.