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论文:2020,Vol:38,Issue(6):1339-1344 |
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引用本文： |
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张钊, 张轶, 黄瑞. 带关键帧和可靠平面表示的激光定位算法[J]. 西北工业大学学报 |
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ZHANG Zhao, ZHANG Yi, HUANG Rui. A New SLAM Algorithm with Key-Frame Estimation and Local Map Upgrade Scheme[J]. Northwestern polytechnical university |
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| 带关键帧和可靠平面表示的激光定位算法 |
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| 张钊, 张轶, 黄瑞 |
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| 四川大学 计算机学院, 四川 成都 610000 |
| 摘要: |
| 激光实时定位与地图构建（simultaneous localization and mapping，SLAM）是创建地图和实时导航的重要手段之一，也是无人驾驶不可缺少的一环。针对目前激光SLAM算法对特征匹配可靠性不足、配准误差较大等问题，基于平面拟合算法，提出一种局部地图改进和关键帧估计的方案。具体包括以下3个方面：①局部地图匹配规则和平面表示方法；②局部地图更新方案；③关键帧筛选机制。该方法解决了目前激光定位方案中缺乏关键帧估计，以及局部地图中平面多向性问题，实验表明该方法使得局部地图能够保留更具多样性的激光雷达帧，同时平面表示和匹配也更为可靠。 |
| 关键词:
SLAM
点云
定位算法
关键帧
无人驾驶
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| A New SLAM Algorithm with Key-Frame Estimation and Local Map Upgrade Scheme |
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| ZHANG Zhao, ZHANG Yi, HUANG Rui |
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| School of Computer Science, Sichuan University, Chengdu 610000, China |
| Abstract: |
| Simultaneous Localization and Mapping(SLAM) is the most important tool in creating map and auto-navigation,which is an indispensable link for pilotless automobile. The current SLAM algorithms suffer from unreliable feature matching and large registration error. To reduce those deficiencies,we proposed a key-frame estimation and local map upgrade scheme,which include the following 3 parts:1) Local map matching strategy; 2) Local map updating scheme; 3) Key-frame selecting scheme. Experimental results proved that our scheme improved the performance of current localization methods. |
| Key words:
laser SLAM
point cloud
localization algorithm
key-frame
auto-drive
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| 收稿日期: 2020-04-23
修回日期:
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| DOI: 10.1051/jnwpu/20203861339 |
| 通讯作者: 张轶(1981-),四川大学副教授,主要从事计算机视觉、机器智能研究。e-mail:yi.zhang@scu.edu.cn
Email：yi.zhang@scu.edu.cn |
| 作者简介: 张钊(1998-),四川大学硕士研究生,主要从事计算机视觉研究。
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| 相关功能 |
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| 作者相关文章 |
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| 张钊 在本刊中的所有文章 |
| 张轶 在本刊中的所有文章 |
| 黄瑞 在本刊中的所有文章 |
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参考文献: |
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