The Design of an Augmented Reality System for Urban Search and Rescue

Runze Wang, Huimin Lu, Junhao Xiao, Yi Li, Qihang Qiu
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引用次数: 5

Abstract

Most robots in urban search and rescue (USAR) fulfill tasks teleoperated by human operators (Such as controlling robot movement to avoid obstacles and explore unknown environments). The operator has to know the location of the robot and find the position of the target (victim). This paper presents an augmented reality system using a Kinect sensor on a customly designed rescue robot. Firstly, Simultaneous Localization and Mapping (SLAM) using RGB-D cameras is running to get the position and posture of the robot. Secondly, a deep learning method is adopted to obtain the location of the target. Finally, we place an AR marker of the target in the global coordinate and display it on the operator's screen to indicate the target even when the target is out of the camera's field of view. The experimental results show that the proposed system can be applied to help humans interact with robots.
城市搜救增强现实系统的设计
在城市搜救(USAR)中,大多数机器人完成由人类操作员远程操作的任务(如控制机器人运动以避开障碍物和探索未知环境)。操作者必须知道机器人的位置,并找到目标(受害者)的位置。本文介绍了一种基于Kinect传感器的增强现实系统。首先,利用RGB-D相机进行同步定位和测绘(SLAM),获取机器人的位置和姿态;其次,采用深度学习方法获取目标位置;最后,我们在全局坐标中放置目标的AR标记,并将其显示在操作员的屏幕上,即使目标不在相机的视野范围内也可以指示目标。实验结果表明,该系统可以应用于人类与机器人的交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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