2.5D激光传感器设计及室内环境特征提取算法研究

Design of 2.5D Lidar Device and Research of Feature Extraction Method for Indoor Environment

在机器人同步定位与地图构建(Simultaneous Localization and Mapping,SLAM)问题中,机器人一般通过激光雷达或视觉传感器来感知环境。视觉传感器受环境光照影响很大,相比之下激光传感器具有测距精度高、性能稳定的优点。为改进普通2D激光雷达数据量小、在SLAM的数据匹配过程中鲁棒性不强的问题,本文设计了一种音圈电机驱动的2. 5D激光传感器。采用电机驱动2D激光雷达在竖直方向上往复运动,通过对2D激光数据和音圈电机编码器的同步实现了空间带状(2. 5D)区域的激光数据采集。当移动机器人工作在半结构化的室内环境中时,可以认为从2. 5D激光传感器获得的高度有限的带状点云具有与地面垂直的先验分布。本文对2. 5D激光传感器采集到的激光点云进行了特征的提取,提取了空间的平面和棱线特征以及竖直方向突变的特征。

In the mobile robot SLAM problem, visual sensor are usually greatly affected by the ambient light. Compared with the visual sensors, the laser sensor has the advantages of high measurement accuracy and high stability. In order to improve the data association performance and the robustness of data matching in SLAM, 2.5D laser device was designed. A Voice Coil Motor was employed to drive the 2D lidar up and down vibrating. With the motor - driven 2D laser lidar reciprocating in the vertical direction, laser data can be acquired in a belt - shaped （2.5 D） region by synchronizing the 2D laser data with the voice coil motor encoder. Since the mobile robot is always working in the semi - structured indoor environment, it can be assumed that the 2.5D lidar point clouds from the 2.5D laser de- vice has a prior distribution perpendicular to the ground. In this paper, the laser point clouds from the 2.5D laser sensor was firstly filtered and then a feature extraction method was proposed to extract the planar patches and spatial edges.