北京航空航天大学学报 ›› 2008, Vol. 34 ›› Issue (06): 613-617.

• 论文 •    下一篇

未知环境下移动机器人单目视觉导航算法

战强, 吴佳   

  1. 北京航空航天大学 机械工程及自动化学院, 北京 100191
  • 收稿日期:2007-07-13 出版日期:2008-06-30 发布日期:2010-09-17
  • 作者简介:战 强(1972-),男,山东青岛人,副教授,qzhan@buaa.edu.cn.
  • 基金资助:

    国家863计划资助项目(2007AA04Z252);国家自然科学基金资助项目(50705003)

Monocular vision-based navigation algorithm for mobile robots in unknown environments

Zhan Qiang, Wu Jia   

  1. School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2007-07-13 Online:2008-06-30 Published:2010-09-17

摘要: 提出了一种未知环境下移动机器人单目视觉导航算法,算法包括障碍物检测、单目视觉测距和局部路径规划3部分.为减小光照等环境因素对基于特征的障碍物检测的影响,对彩色图像在HSI颜色空间中用基于像素的直方图比较进行分割,获取障碍物轮廓序列的图像坐标点集.在单目视觉测距中,通过几何关系推导法建立图像坐标系和机器人坐标系间的变换关系,进而实现由障碍物图像位置计算其与机器人间的实际距离.局部路径规划对摄像机梯形视场区域转换后的矩形区域建立模型划分栅格,由障碍物轮廓序列图像坐标和单目视觉测距计算构建障碍物栅格图,并用提出的栅格搜索算法搜索障碍物栅格图,得到机器人安全行驶路径.实际环境中进行的实验结果表明,算法能有效减小反光、阴影等的影响,在未知环境中正确规划出机器人局部可行路径实现导航.

Abstract: A monocular vision-based navigation algorithm for mobile robots moving in unknown environments was presented, which consists of obstacle detection, monocular vision based distance measurement and local path planning. In order to decrease the impact of lighting disturbance on obstacle detection, pixel-based image segmentation in HSI color space was used to get the set of the image coordinates of the obstacle boundaries by comparing histograms of current image window and reference image window. In order to realize distance measuring between obstacles and a robot, a transformation equation between the vision coordinates and the robot coordinates was deduced by geometrical reasoning. Grid map was used to model the rectangular area transformed from the trapezoidal field of view of the camera and grids with obstacles were marked according to the obstacle boundaries and the measured distance. With a new searching method a safe local path for the robot was found by searching the grid map. Experiments done in real environments show that less sensitive to highlight and shading, the proposed algorithm could correctly plan a safe local path to navigate the robot.

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