Vision-based detection methods often require consideration of the robot’s sight. For example, panoramic images cause image distortion, which negatively affects the target recognition and spatial localization. Furthermore, the original you only look once method does not have a reasonable performance for the image recognition in the panoramic images. Consequently, some failures have been reported so far when implementing the visual recognition on the robot. In the present study, it is intended to optimize the conventional you only look once algorithm and propose the modified you only look once algorithm. Comparing the obtained results with the experiment shows that the modified you only look once method can be effectively applied in the graphics processing unit to reach the panoramic recognition speedup to 32 frames rate per second, which meets the real-time requirements in diverse applications. It is found that the accuracy of the object detection when applying the proposed modified you only look once method exceeds 70% in the studied cases.

中文翻译：

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服务机器人视觉识别算法优化

基于视觉的检测方法通常需要考虑机器人的视线。例如，全景图像会导致图像失真，从而对目标识别和空间定位产生负面影响。此外，原始的你只看一次方法对于全景图像中的图像识别没有合理的性能。因此，到目前为止，在机器人上实施视觉识别时已经报告了一些失败。在本研究中，旨在优化传统的只看一次算法，并提出修改后的只看一次算法。将得到的结果与实验对比表明，修改后的you only look once方法可以有效地应用于图形处理单元，达到每秒32帧的全景识别速度，满足各种应用的实时性要求。结果发现，在所研究的案例中，应用所提出的修改后的你只看一次方法时物体检测的准确率超过了 70%。