Target Locating of Robots Based on the Fusion of Binocular Vision and Laser Scanning

Ze Lv, Lecai Cai, Zhiming Wu, Kui Cheng, B. Chen, Keyuan Tang
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Abstract

The accuracy of target locating for vision-based robots would be affect by environment factors such as light. In order to solve the problem, we proposed a target locating method based on binocular vision locating technology, together with laser scanning positioning technology, considering that laser scanning can obtain three-dimensional environmental information with high definition, and is little influenced by light. In this method, the binocular vision pixel image and the laser scanning point cloud image are first jointly calibrated to map the image pixels with the point cloud data; secondly, the visual image and the laser two-dimensional depth map are detected separately using YOLOv3; then, a decision-level fusion method is utilized to fuse point cloud depth image and the camera image; finally, YOLOv3 is used to detect bound box and confidence of the fused map. The results show that the proposed method has the ability to locate object accurately.
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基于双目视觉与激光扫描融合的机器人目标定位
视觉机器人的目标定位精度会受到光线等环境因素的影响。为了解决这一问题,考虑到激光扫描可以获得三维环境信息,且清晰度高,受光的影响小,我们提出了一种基于双目视觉定位技术和激光扫描定位技术的目标定位方法。该方法首先对双目视觉像素图像和激光扫描点云图像进行联合标定,将图像像素与点云数据进行映射;其次,利用YOLOv3分别检测视觉图像和激光二维深度图;然后,采用决策级融合方法对点云深度图像与相机图像进行融合;最后,利用YOLOv3对融合图的界框和置信度进行检测。结果表明,该方法具有准确定位目标的能力。
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