.png){kind=icon}
返回
Energy-Efficient SVM Learning Control System for Biped Walking Robots
.png){kind=icon}
PRE
AI
DOI：10.1109/TNNLS.2013.2242486.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
An energy-efficient support vector machine (EE-SVM) learning control system considering the energy cost of each training sample of biped dynamic is proposed to realize energy-efficient biped walking. Energy costs of the biped walking samples are calculated. Then the samples are weighed with the inverses of the energy costs. An EE-SVM objective function with energy-related slack variables is proposed, which follows the principle that the sample with the lowest energy consumption is treated as the most important one in the training. That means the samples with lower energy consumption contribute more to the EE-SVM regression function learning, which highly increases the energy efficiency of the biped walking. Simulation results demonstrate the effectiveness of the proposed method.
Keyword:
Biped robot
energy cost
learning control
support vector machine (SVM)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.9
论文数:
7.6K
被引数:
7.2W
机构
引用论文
Feedback Control of Planar Biped Robot With Regulable Step Length and Walking Speed具有可调节步长和步行速度的平面双足机器人反馈控制
PREAI
分享收藏Weighted least squares support vector machines: robustness and sparse approximation.png)
NEUROCOMPUTING
OAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏
查看更多内容