| 同步定位与建图技术发展综述 |
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| 引用本文： | 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. |
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| 作者姓名： | 吴建清 宋修广 |
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| 作者单位： | 山东大学齐鲁交通学院, 山东 济南 250002 |
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| 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。
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| 关 键 词： | SLAM 定位 建图 多传感器融合 深度学习 相机 激光雷达 |
| 收稿时间： | 2021-04-12 |
Review on development of simultaneous localization and mapping technology |
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| Jianqing WU,Xiuguang SONG.Review on development of simultaneous localization and mapping technology[J].Journal of Shandong University of Technology,2021,51(5):16-31. |
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| Authors: | Jianqing WU Xiuguang SONG |
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| Affiliation: | School of Qilu Transportation, Shandong University, Jinan 250002, Shandong, China |
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| 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. |
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| Keywords: | SLAM localization mapping multi-sensor fusion deep learning camera lidar |
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