Neural network based control of legged hopping systems
Neural network based control of legged hopping systems
复制标题
基于神经网络的腿式跳跃系统控制
DOI：
10.1109/isic.2001.971494
复制
发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Klaus D. Maier
中科院分区：
文献类型：
--
作者：
Klaus D. Maier
研究了基于生物跳跃和奔跑动力学的运动系统模型控制问题。这个运动系统仅仅由一个连接到点质量上的无质量弹簧组成。它描述了一种在平坦的地面上快速的三维腿部运动。快速移动的腿自主系统需要不同的硬件布局和控制方法，这与缓慢移动的系统形成了鲜明对比。弹簧质量系统是描述这一原理运动和原理控制任务的模型。多层感知器被用来实现适合于这种运动系统的神经控制器。它们被证明适合于用相对较少的神经元来精确控制运动。弹簧-质量系统的环境从均匀地变为不均匀地的实验也证明了这一点。神经控制器在没有接受过训练的情况下表现良好。
Controlling the model of a movement system based on the dynamics of biological hopping and running is investigated. This movement system consists merely of a massless spring attached to a point mass. It describes a fast three-dimensional legged locomotion on even grounds. Rapidly moving legged autonomous systems require different hardware layouts and control approaches in contrast to slow moving ones. The spring mass system is a model that describes this principle movement as well as the principle control task. Multilayer-perceptrons are used to implement neurocontrollers suitable for such a movement system. They are proved to be suitable for exact control of the movement with a relatively small number of neurons. This is also shown by an experiment where the environment of the spring-mass system has been changed from even to uneven ground. The neurocontroller performs well without being trained for it.
影响因子：
2.4
作者：
BLICKHAN, R
通讯作者：
BLICKHAN, R