Binocular Vision Obstacle Detection System of Wall Climbing Robot
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摘要: 针对壁面障碍物的不确定性，设计了一种爬壁机器人双目视觉障碍检测系统。具体包括搭建双目平行视觉系统，根据双目视觉理论对摄像机进行标定，获取相机标定参数；通过标定参数和极线约束对双目图像进行校正，解决图像畸变不共面问题；利用块搜索模型和相似度函数获取视差，保证视差获取的快速性与鲁棒性；最后提出一种障碍物检测算法：建立壁面检测模型约束检测范围，引入面积阈值，过滤干扰并实现障碍物提取，提出一种障碍物定位算法，通过宽度、深度与偏距三个方面对障碍物进行定位，同时，通过线性插值解决障碍物中心视差丢失问题。实验结果表明：在保证实时性的基础上，该系统能够有效检测前方障碍物且准确提取率能够达到95.9%，定位误差为4.91%，满足爬壁机器人检测要求。Abstract: Aiming at the uncertainty of wall obstacles, the wall climbing robot obstacle detection system based on the binocular vision is designed. Firstly, a binocular parallel vision system is built to calibrate the camera according to in terms of the binocular vision theory, and the camera calibration parameters is obtained. Then, the binocular images are corrected with the calibration parameters and the non-coplanar image distortion is solved with the epipolar constraints. Then the parallax is obtained with the block search model and similarity function to ensure the rapidity and robustness of parallax acquisition. Finally, an obstacle detection algorithm is proposed, in which the wall detection model is established to constrain the detection range, the area threshold is introduced to filter the interference and extract the obstacles. An obstacle location algorithm is proposed, which locates the obstacle in three aspects: width, depth and offset. At the same time, the parallax loss problem in the center of the obstacle is solved with the linear interpolation. The experimental results show that on the basis of the real-time performance, the system can effectively detect obstacles and the accurate extraction rate can reach 95.9% and the positioning error is 4.91%. It meets the requirements of wall-climbing robot detection.
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Key words:
- obstacle detection /
- binocular vision /
- climbing robot
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表 1 视差插值数据
序号 视差di 判断异常 视差均值dd(剔除异常值后) 中心点视差do 稳定点视差与搜索距离 中心点视差(插值后) 插值误差/% 1 1 685 正常 1 692 -16 lr=35
ll=33
dl=1 696
dr=1 7001 698 0.35 2 1 705 正常 3 1 681 正常 4 -16 异常 5 1 683 正常 6 1 703 正常 7 1 692 正常 8 -16 异常 9 1 684 正常 10 1 701 正常 
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表 2 误差数据
深度/m 深度误差/% 偏距误差/% 宽度误差/% 定位误差/% 0.6 1.90 3.26 7.61 4.26 0.9 2.04 3.90 7.84 4.59 1.2 2.12 4.53 8.12 4.92 1.5 2.30 4.98 8.43 5.24 1.8 2.56 5.32 8.75 5.54 平均 2.18 4.40 8.15 4.91
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