文献类型：会议论文

英文题名：The field terrain recognition based on extreme learning machine using wavelet features

作者：Liu, Caixia[1];Fang, Jianjun[1];Liu, Yanxia[1];Lu, Yujiao[1]

通讯作者：Liu, CX[1]

机构：[1]Beijing Union Univ, Sch Automat, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Sch Automat, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：IEEE International Conference on Mechatronics and Automation (ICMA)

会议日期：AUG 06-09, 2017

会议地点：Takamatsu, JAPAN

语种：英文

外文关键词：Legged robots; Extreme learning machine; Wavelet feature; Terrain recognition

摘要：Feature extraction and classification algorithm is important to determine the accuracy of classification. The terrain recognition of a legged robot has higher requirements on real-time classification. Considering the traditional training methods is difficult to meet the requirements, this paper applies the extreme learning machine using wavelet features to terrain recognition. The experimental results show that recognition rate of the extreme learning algorithm is 96.78%, which is 30.89% and 20.45% higher than BP and SVM algorithm respectively. Hence, the proposed method in this paper has obvious advantages over traditional algorithm in parameter selection and learning speed.