基于图像的变电站巡检机器人精确对准

J. Liu, Ming Nie, Hao Wu, Xiaoming Mai
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引用次数: 2

摘要

基于激光测距的SLAM导航定位算法的精度,特别是在复杂场景下,不能满足自动抄表和隔离开关状态读取的精度要求。提出了一种基于单目摄像机的变电站巡检机器人PTZ精确对准方法。通过预捕获的参考图像确定机器人的期望位置和PTZ(Pan Tilt Zoom)相机的方向。采用尺度不变特征变换(SIFT)算法对当前视图和参考图像进行匹配,提取视觉反馈信息。采用随机样本一致性(RANSAC)算法求解当前图像与参考图像之间的仿射变换。通过对PTZ控制平台的控制信号和图像的特征空间进行处理,得到代表映射关系的雅可比矩阵。结合图像的多尺度变换,实现了PTZ的精确对准。在室外变电站实际环境下的实验结果验证了该处理方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An image-based Accurate Alignment for Substation Inspection Robot
The precision of SLAM navigation positioning algorithm based on laser ranging, especially in complex scenes, is not satisfied to meet the accuracy requirements for automatic meter reading and isolating switch status reading. A method of PTZ accurate alignment for substation inspection robot is based on monocular vision camera is proposed. The desired position of robot and orientation of PTZ(Pan Tilt Zoom) camera are defined by the pre-capture reference image. The Scale Invariant Feature Transform (SIFT) algorithm is applied to extract the visual feedback information by matching the current view and the reference image. A Random Sample Consensus (RANSAC) algorithm is used to solve the affine transform between the current and reference image. The Jacobian matrix, representing the mapping relationship, is created by processing control signal of the PTZ control platform and feature space for the image. Besides this, PTZ accurate alignment is realized combined with the image multi-scale transformation. The experiment results of a realistic outdoor substation environment demonstrate the effectiveness of the processed method.
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