To tackle the water surface pollution problem, a vision-based water surface garbage capture robot has been developed in our lab. In this article, we present a modified you only look once v3-based garbage detection method, allowing real-time and high-precision object detection in dynamic aquatic environments. More specifically, to improve the real-time detection performance, the detection scales of you only look once v3 are simplified from 3 to 2. Besides, to guarantee the accuracy of detection, the anchor boxes of our training data set are reclustered for replacing some of the original you only look once v3 prior anchor boxes that are not appropriate to our data set. By virtue of the proposed detection method, the capture robot has the capability of cleaning floating garbage in the field. Experimental results demonstrate that both detection speed and accuracy of the modified you only look once v3 are better than those of other object detection algorithms. The obtained results provide valuable insight into the high-speed detection and grasping of dynamic objects in complex aquatic environments autonomously and intelligently.

中文翻译：

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一种改进的基于视觉的水面垃圾捕获机器人YOLOv3检测方法

为了解决水面污染问题，我们实验室开发了一种基于视觉的水面垃圾捕获机器人。在本文中，我们提出了一种改进的基于 v3 的垃圾检测方法，允许在动态水生环境中进行实时和高精度的对象检测。更具体地说，为了提高实时检测性能，你只看一次 v3 的检测尺度从 3 简化为 2。此外，为了保证检测的准确性，我们训练数据集的锚框被重新聚类以替换一些在原始版本中，您只查看一次不适合我们的数据集的 v3 先前锚框。凭借所提出的检测方法，抓捕机器人具备了清扫现场漂浮垃圾的能力。实验结果表明，修改后的you only look once v3的检测速度和准确率均优于其他物体检测算法。获得的结果为在复杂的水生环境中自主和智能地高速检测和抓取动态物体提供了宝贵的见解。