XIE Xing-zhe, WANG Heng, LIU Ran, et al. Obstacle height detection based on binocular stereovision[J]. 2010, 29(7): 118-120+130. DOI: 10.13873/j.1000-97872010.07.018.
基于双目视觉的障碍物高度检测
摘要
针对变电站设备巡检机器人的应用需求
提出了一种基于双目视觉的障碍物高度检测方法。采用双目测距原理对障碍物的距离信息进行检测
然后在图像中选择样本点
根据这些点在视差图中的三维坐标
利用改进的RANSAC算法
求取当前帧的路面的平面方程
并利用Kalman滤波对此平面方程进行估计和预测。最后利用点到平面距离公式求取障碍物的高度
得到三维环境的高度图
利用高度信息检测障碍物。实际应用表明:提出的方法能有效地克服光照变化和阴影对障碍物检测的影响
所求得障碍物的高度信息精度较高
能够满足需求
对于环境变化的适应性较强。
Abstract
An original approach for the patrol robot in the substation to detect the obstacle height is presented based on binocular stereovision. The road model hypothesis of the robot’s environment is proposed. The distance between the obstacle and the camera is computed on the basis of the algorithm of binocular distance measurement. With the selected sample in the disparity image
the road plane equation of the current frame is calculated by the improved random sample consensus( RANSAC) algorithm and estimated and predicted by the Kalman filter. When the distance between the obstacle and the road is calculated on the basis of the formula from the point to the plane
the height image is obtained. The obstacle is detected according to the height information. Applications show that the algorithm is robust to the shadows and illumination change and more adaptable to the environment. The obstacle height is precise enough to meet the requirement.
An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments [J] . Hartmut Surmann,Andreas Nüchter,Joachim Hertzberg. Robotics and Autonomous Systems . 2003 (3)