Detecting glass in Simultaneous Localisation and Mapping
Detecting glass in Simultaneous Localisation and Mapping
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DOI：
10.1016/j.robot.2016.11.003
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发表时间：
2017-02-01
影响因子：
4.3
通讯作者：
Wang, JianGuo
中科院分区：
文献类型：
--
作者：
Wang, Xun;Wang, JianGuo
同步定位与地图构建（SLAM）技术已成为先进机器人平台的关键技术之一。目前最先进的室内SLAM与激光扫描测距仪可以提供准确的实时定位和地图服务的移动的机器人平台，如PR2机器人。近年来，许多现代建筑设计都将大型玻璃面板作为关键的内部装修元素之一，例如大型玻璃墙。由于玻璃面板的透明性，激光测距仪无法产生准确的读数，这导致SLAM在这些环境中无法正常工作。在本文中，我们提出了一个简单而有效的解决方案来识别玻璃面板的基础上镜面反射的激光束从玻璃。具体来说，我们使用一个简单的技术来检测周围的正常入射角的玻璃面板的反射光强度分布。将这种玻璃检测方法与现有的SLAM算法相结合，我们的SLAM系统能够实时检测和定位玻璃障碍物。此外，我们在两座办公楼中使用PR2机器人进行的测试表明，所提出的方法可以检测到95%的玻璃面板，没有误报检测。带有玻璃检测的修改后SLAM的源代码作为开源ROS包沿着发布。皇冠版权所有（C）2016由Elsevier B.V.出版。保留所有权利。
Simultaneous Localisation and Mapping (SLAM) has become one of key technologies used in advanced robot platform. The current state-of-art indoor SLAM with laser scanning rangefinders can provide accurate realtime localisation and mapping service to mobile robotic platforms such as PR2 robot. In recent years, many modern building designs feature large glass panels as one of the key interior fitting elements, e.g. large glass walls. Due to the transparent nature of glass panels, laser rangefinders are unable to produce accurate readings which causes SLAM functioning incorrectly in these environments. In this paper, we propose a simple and effective solution to identify glass panels based on the specular reflection of laser beams from the glass. Specifically, we use a simple technique to detect the reflected light intensity profile around the normal incident angle to the glass panel. Integrating this glass detection method with an existing SLAM algorithm, our SLAM system is able to detect and localise glass obstacles in realtime. Furthermore, the tests we conducted in two office buildings with a PR2 robot show the proposed method can detect' 95% of all glass panels with no false positive detection. The source code of the modified SLAM with glass detection is released as a open source ROS package along with this paper. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.