面向机器人导航与测绘的多传感器融合玻璃检测

Hao Wei, Xue-En Li, Ying Shi, Bo You, Yi Xu
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引用次数: 17

摘要

同时定位与绘图(SLAM)已成为机器人的基本功能,但现有的SLAM算法在玻璃环境中无法稳定地工作,特别是在使用低成本传感器时。本文提出了一种基于超声和激光扫描数据的多传感器融合技术的高效、鲁棒的玻璃检测方法。通过将玻璃检测算法与SLAM相结合,我们改进了现有的SLAM算法,以提供更精确的制图和定位结果。在此基础上,提出了一种新的机器人导航方法,并在机器人平台上进行了实验,实验表明,新的导航框架使机器人在玻璃环境下的导航效率提高了11%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-sensor Fusion Glass Detection for Robot Navigation and Mapping
Simultaneous Localization and Mapping(SLAM) has become an essential function of the robot, but existing SLAM algorithms cannot work robustly and stably in a glass environment, especially when using low cost sensors. In this paper, we propose an efficient and robust method to detect glass based on multi-sensor fusion technology of ultrasonic and laser scan data. By integrating the glass detection algorithm with SLAM, we have improved an existing SLAM algorithm to provide more accurate mapping and localization results. On this basis, we proposed a new robot navigation method and experimented on the robot platform, the experiments show that the new navigation frame increased robot navigation efficiency by 11% in glass environment.
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