Mobile Robot Navigation Using an Object Recognition Software with RGBD Images and the YOLO Algorithm
Mobile Robot Navigation Using an Object Recognition Software with RGBD Images and the YOLO Algorithm
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DOI：
10.1080/08839514.2019.1684778
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发表时间：
2019-11-02
影响因子：
2.8
通讯作者：
Tello Gamarra, Daniel Fernando
中科院分区：
文献类型：
--
作者：
Dos Reis, Douglas Henke;Welfer, Daniel;Tello Gamarra, Daniel Fernando
这项工作提出了一个基于YOLO算法的视觉系统，用于识别移动机器人路径上可能成为障碍物的静态物体。为了识别物体及其距离，使用了微软Kinect传感器。此外，采用Nvidia Jetson TX2 GPU提高了图像处理算法的性能。我们的实验结果表明，YOLO网络能够检测出所有预先训练好的障碍物，并且具有良好的可靠性，使用微软Kinect相机返回的深度信息计算距离的误差在3.64%以下。
This work presents a vision system based on the YOLO algorithm to identify static objects that could be obstacles in the path of a mobile robot. In order to identify the objects and its distances, a Microsoft Kinect sensor was used. In addition, a Nvidia Jetson TX2 GPU was used to increase the image processing algorithm performance. Our experimental results indicate that the YOLO network has detected all the predefined obstacles for which it has been trained with good reliability and the calculus of the distance using the depth information returned by the Microsoft Kinect camera had an error below of 3,64%.