A new multisensor fusion SLAM approach for mobile robots  

作　　者：Fang FANG Xudong MA Xianzhong DAI Kun QIAN 

机构地区：[1]Key Laboratory of Measurement and Control of CSE, School of Automation, Southeast University, Nanjing Jiangsu 210096, China

出　　处：《控制理论与应用（英文版）》2009年第4期389-394,共6页

基　　金：supported by the National Natural Science Foundation of China (No.60805032);the National High Technology Research and Development Program (No.2006AA040202, 2007AA041703)

摘　　要：This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.

关 键 词：多传感器融合 移动机器人 HOUGH变换 声纳系统 视觉特征 CCD相机 传感器检测 外部机制 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP242[自动化与计算机技术—控制科学与工程]