张奇, 顾伟康. 基于多传感器数据融合的环境理解及障碍物检测算法[J]. 机器人, 1998, 20(2): 104-110.
引用本文: 张奇, 顾伟康. 基于多传感器数据融合的环境理解及障碍物检测算法[J]. 机器人, 1998, 20(2): 104-110.
ZHANG Qi, GU Weikang. ALGORITHMS OF ENVIRONMENT UNDERSTANDING AND OBSTACLE DETECTION BASED ON MULTISENSOR DATA FUSION[J]. ROBOT, 1998, 20(2): 104-110.
Citation: ZHANG Qi, GU Weikang. ALGORITHMS OF ENVIRONMENT UNDERSTANDING AND OBSTACLE DETECTION BASED ON MULTISENSOR DATA FUSION[J]. ROBOT, 1998, 20(2): 104-110.

基于多传感器数据融合的环境理解及障碍物检测算法

ALGORITHMS OF ENVIRONMENT UNDERSTANDING AND OBSTACLE DETECTION BASED ON MULTISENSOR DATA FUSION

  • 摘要: 本文研究了移动机器人中基于Dempster-Shafer证据推理理论的多传感器数据融合技术.通过融合由CCD彩色摄像机获取的2D彩色图像及由激光测距成像雷达获取的3D距离图像,移动机器人的环境理解及障碍物检测的可靠性与精度比在任何单一传感器所获得的信息的基础上有了很大的提高.文中探讨了移动机器人中视觉信息融合的许多具有较大难度的实际问题,取得了有意义的结果.

     

    Abstract: Based on Dempster Shafer theory of evidence inference, this paper presents some algorithms of multisensor data fusion for mobile robots. By integrating the 2D data and the 3D data that are both the pre processed information obtained by a color CCD camera and a laser imaging tange sensor respectively, the accuracy and the reliability of environment understanding and obstacle detection for mobile robot are improved than those based only on any single sensory information. Some difficult problems of vision information fusion for mobile robot are discussed, and meaningful expermental results of fusion on unstructured road network are obtained.

     

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