基于改进支持向量回归算法的移动机器人定位.docxVIP

基于改进支持向量回归算法的移动机器人定位 　　摘要：　　为了提高移动机器人定位精度，提出了一种基于正交编码器和陀螺仪的轮式移动机器人定位系统，建立机器人的定位模型和运动学模型。研究了支持向量回归算法，为获得更好的鲁棒性，对目标函数误差平方进行加权，分析不同参数优化算法对支持向量机回归准确率的影响。以自制的移动机器人为实验平台，将改进的算法与最小二乘支持向量回归算法、加权最小二乘支持向量回归算法进行比较，对比了用改进算法时机器人在木地板场地与瓷砖场地的定位误差情况，并对正交编码器+陀螺仪定位系统与双码盘定位系统、单码盘+陀螺仪定位系统进行比较。实验结果表明，改进的算法使机器人的定位精度明显高于对比算法，并且所提出的定位系统定位效果较好。　　关键词：　　机器人；定位模型；运动模型；加权最小二乘支持向量回归算法；定位精度　　中图分类号：　　TP242　　文献标志码：A　　Abstract：　　In order to improve the positioning accuracy of mobile robots， a kind of positioning system for wheeled mobile robots based on orthogonal encoder and gyroscope was proposed， and the positioning model and kinematics model of robot were established. With the purpose of obtaining better robustness， Support Vector Regression algorithm was studied， the error square of objective function was weighted， and the effect of different parameter optimization algorithms on the accuracy of SVR were analyzed. The experimental platform was established by homemade mobile robot， the Least Squares Support Vector Regression algorithm and the Weighted Least Squares Support Vector Regression algorithm were compared with the improved algorithm. The positioning errors of the improved algorithm when the robot worked on ceramic and wood floor were compared， and the orthogonal encoder plus gyroscope positioning system was compared with the double encoder positioning system and the single encoder plus gyroscope positioning system. The experimental results show that the robot positioning accuracy of the improved algorithm is higher than comparison algorithms， and the proposed positioning system has a better location performance.　　英文关键词Key words：　　robot； localization model； kinematic model； Weighted Least Squares Support Vector Regression algorithm； positioning accuracy　　0引言　　机器人是一门综合性的交叉学科，涉及多方面的研究领域，包括机械结构设计、图像处理、自动控制、人工智能以及定位技术等，且适用于一些危险、肮脏、狭小等场所。随着传感器机器技术的不断发展，机器人的应用领域越来越广泛，特别是自主移动机器人逐渐受到众多学者的关注。自主移动机器人能够根据其内部所存储的地图以及外部传感器提供信息实现自主定位，正成为智能机器人的研究热点[1-2]。　　移动机器人应该能够解决导航中的三大问题，即：“我在哪里” “