Institute of Human Performance Research Laboratories, The University of Hong Kong, 1/F., Patrick Manson Building, 7 Sassoon Road, Pokfulam, Hong Kong.
Neural Netw. 2010 Apr;23(3):452-60. doi: 10.1016/j.neunet.2009.11.003. Epub 2009 Dec 3.
Biped humanoid robots have gained much popularity in recent years. These robots are mainly controlled by two major control methods, the biologically-inspired approach based on Central Pattern Generator (CPG) and the engineering-oriented approach based on Zero Moment Point (ZMP). Given that flexibility in the body torso is required in some human activities, we believe that it is beneficial for the next generation of humanoid robots to have a flexible spine as humans do. In order to cope with the increased complexity in controlling this type of robot, a new kind of control system is necessary. Currently, there is no controller that allows a flexible spine humanoid robot to maintain stability in real-time while walking with dynamic spine motions. This paper presents a new hybrid CPG-ZMP control system for the walking of a realistically simulated flexible spine humanoid robot. Experimental results showed that using our control method, the robot is able to adapt its spine motions in real-time to allow stable walking. Our control system could be used for the control of the next generation humanoid robots.
双足人形机器人近年来越来越受欢迎。这些机器人主要通过两种主要的控制方法进行控制，一种是基于中枢模式发生器（CPG）的仿生方法，另一种是基于零力矩点（ZMP）的工程方法。考虑到在某些人类活动中需要身体躯干的灵活性，我们认为下一代人形机器人具有像人类一样的灵活脊柱将是有益的。为了应对控制这种类型机器人的复杂性增加，需要一种新的控制系统。目前，没有控制器可以允许具有灵活脊柱的人形机器人在进行动态脊柱运动的同时实时保持稳定性。本文提出了一种新的混合 CPG-ZMP 控制系统，用于模拟真实灵活脊柱的人形机器人的行走。实验结果表明，使用我们的控制方法，机器人能够实时适应其脊柱运动，从而实现稳定行走。我们的控制系统可用于下一代人形机器人的控制。
