论文标题
Covy：具有复合视觉系统的AI驱动机器人，用于检测社会疏远的违规行为
Covy: An AI-powered Robot with a Compound Vision System for Detecting Breaches in Social Distancing
论文作者
论文摘要
本文介绍了一个复合视觉系统，该系统使机器人可以使用廉价的相机将高达15m的人定位。而且，它提出了一个强大的导航堆栈，将深度加固学习（DRL）和一种概率定位方法结合在一起。为了测试这些系统的疗效，我们原型制定了我们称为Covy的低成本移动机器人。 Covy可用于应用程序，例如在大流行过程中促进社会疏远或估计人群的密度。我们通过在模拟环境和现实环境中进行的大量实验评估了Covy的性能。我们的结果表明，Covy的复合视觉算法使使用的深度摄像头的范围翻了一番，并且其混合导航堆栈比基于纯的DRL摄像机更强大。
This paper introduces a compound vision system that enables robots to localize people up to 15m away using a cheap camera. And, it proposes a robust navigation stack that combines Deep Reinforcement Learning (DRL) and a probabilistic localization method. To test the efficacy of these systems, we prototyped a low-cost mobile robot that we call Covy. Covy can be used for applications such as promoting social distancing during pandemics or estimating the density of a crowd. We evaluated Covy's performance through extensive sets of experiments both in simulated and realistic environments. Our results show that Covy's compound vision algorithm doubles the range of the used depth camera, and its hybrid navigation stack is more robust than a pure DRL-based one.
