同步定位与建图技术发展综述

doi:10.6040/j.issn.1672-3961.0.2021.168

摘要/Abstract

摘要：

同步定位与建图(simultaneous localization and mapping, SLAM)技术作为智慧交通领域研究的热点, 是无人驾驶车辆自主规划路径的关键。围绕SLAM技术相关传感器类型、定位、制图、多传感器融合四方面, 从优缺点、适用范围、概率算法、地图类型及融合方式出发, 介绍SLAM技术实现过程中的各个环节, 系统阐述了国内外相关的研究成果。基于多传感器融合SLAM, 分析了目前常见的融合SLAM技术难题, 对SLAM技术的未来发展趋势及实际工程应用做出展望。

关键词: SLAM, 定位, 建图, 多传感器融合, 深度学习, 相机, 激光雷达

Abstract:

As a hot spot in the field of intelligent transportation, simultaneous localization and mapping (SLAM) technology is the key to autonomous path planning for self-driving vehicles. This review focused on four parts with introduction of sensors related to SLAM technology, localization, mapping, and multi-sensor integration. Each step of realization for SLAM technology was introduced from advantages and disadvantages, range of application, probability algorithm, types of map, and integration methods. Based on the investigation of relevant researches about multi-sensor integration, common problems of SLAM technology were analyzed, future development trend and practical engineering application of SLAM technology were prospected.

Key words: SLAM, localization, mapping, multi-sensor fusion, deep learning, camera, lidar

中图分类号:

TQ028

吴建清,宋修广. 同步定位与建图技术发展综述[J]. 山东大学学报 (工学版), 2021, 51(5): 16-31.

Jianqing WU,Xiuguang SONG. Review on development of simultaneous localization and mapping technology[J]. Journal of Shandong University(Engineering Science), 2021, 51(5): 16-31.

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传感器类型		优点	缺点
相机	单目相机	操作简单、成本较低	无法采集深度信息
	多目相机	可获取运动与静止状态下目标的深度信息	标定与计算过程相对复杂、计算量较大
	深度相机	可获取物体的色彩与深度信息、数据采集速度快、数据量更丰富	易受视场角与分辨率影响
激光雷达	2D激光雷达	适用于平面信息采集	感知数据缺乏高度信息，难以成像
激光雷达	3D激光雷达	感知数据具备目标的高度、距离信息，能够还原物体形状，可实现全天候工作	价格昂贵、易受雨雪雾霾等天气影响
惯性测量单元		采集目标加速度、姿态角信息	易产生累积误差
毫米波雷达		对于雨雪雾霾等穿透力强	数据精度低、多冲波段下工作性能会大幅降低
超声波雷达		耗能缓慢、在介质中传播距离远、价格便宜	传输速度极易受天气影响、传输速度相对较慢
红外热成像仪		信息感受更直观、不受电磁影响、作用距离相对较远、全天候环境感知	成本高、不能穿透玻璃制品、存在图片分辨率低与信息对比度小的问题

地图表示类型	优点	缺点
拓扑地图	适用于范围广且障碍物类型较少的场景、占用内存小、计算效率高、路径规划高效	路径规划最优性差、相似物体分辨准确度低
几何信息地图	简化环境信息、障碍物辨识更直观、目标提取更方便	广域环境中数据精度低、计算量大
栅格地图	不受环境地形影响、感知数据易保存与维护	保存数据过多会导致信息更新难度加大、目标识别效果变差

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