基于楼宇场景分类的激光导航与地图构建  

Laser Navigation and Mapping Based on Building Environment Classification

作　　者：宋薇[1] 梁晶 张海桥 沈林勇[1] 章亚男[1] 周洋[3] Song Wei;Liang Jing;Zhang Haiqiao;Shen Linyong;Zhang Ya’nan;Zhou Yang(School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China;State Key Laboratory of Mechanical Transmissions,Chongqing University,Chongqing 400044,China;Joint Laboratory of High Power Laser and Physics,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800,China)

机构地区：[1]上海大学机电工程与自动化学院,上海200444 [2]重庆大学机械传动国家重点实验室,重庆400044 [3]中国科学院上海光学精密机械研究所高功率激光物理联合实验室,上海201800

出　　处：《激光与光电子学进展》2021年第14期96-103,共8页Laser & Optoelectronics Progress

摘　　要：提出一种基于Adaboost算法的楼宇场景分类方法,用于移动机器人在未知楼宇环境中进行自主环境感知和地图构建。所提方法采用激光传感器获得环境局部栅格地图,并对该地图进行特征提取;然后利用Adaboost算法构建场景分类器,针对不同场景选择有效边界点;采用基于边界的遍历式路径规划策略,由边界点确定移动机器人的导航路径。实验结果表明,移动机器人能够在未知楼宇环境中进行自主巡视,并利用自带的同步定位与建图(SLAM)技术将探测到的局部栅格地图拼接为完整的楼宇环境地图,实现自主导航。In this paper,we propose a building environment classification method based on the Adaboost algorithm for autonomous environment perception and mapping of mobile robots in unknown building environments.In the proposed method,laser sensor is used to obtain the raster map of local environment,whose features are extracted.Then,the Adaboost algorithm is used to construct a scene classifier by selecting representative boundary points of different scenarios.We use a boundary-based path planning strategy,in which boundary points determine the navigation path of a mobile robot.Experimental results show that a mobile robot can conduct autonomous inspection in unknown building environments.Simultaneously,the detected local raster maps are spliced into a complete building environment map using built-in simultaneous localization and mapping(SLAM)technology to realize autonomous navigation.

关 键 词：探测器 自主导航 激光传感器 地图构建 楼宇场景分类 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]