计算机工程与应用2011，Vol.47Issue(23)：242-244,248,4.DOI:10.3778/j.issn.1002-8331.2011.23.068
基于支持向量机和Q学习的移动机器人导航
Mobile robot navigation based on support vector machine and Q-learning
摘要
Abstract
Continuous Q-leaming algorithm based on neural has been used in robotic navigation domain for its simplicity and well-developed theory.Aiming at the neural easily falling into local minimum,a new mobile robot navigation method using Q-learning based on a Support Vector Machine (SVM) is proposed.According to the developed mobile robot CASIA-I and its working environment,an approach is proposed,used to determine the reward/penalty function of Q-learning.A SVM is used to estimate the Q-value of state-action pair on-line,at the same time,in order to decrease the on-time learning time of SVM, a sliding time-window is introduced.Experimental results are included to show that the action policy obtained through Q-learning based on SVM can make the mobile robot reach the destination without obstacle collision.关键词
移动机器人/Q学习/支持向量机/导航/在线学习Key words
mobile robot/Q-learning/support vector machine/navigation/on-line learning分类
信息技术与安全科学引用本文复制引用
侯艳丽..基于支持向量机和Q学习的移动机器人导航[J].计算机工程与应用,2011,47(23):242-244,248,4.基金项目
河南省科学技术厅基础与前沿技术研究计划项目(No.102300410242) （No.102300410242）
河南省教育厅自然科学基金项目(No.2010A510009) （No.2010A510009）
河南省科技厅科技发展计划项目(No.112300410210). （No.112300410210）
