Optimized-SC-F-LOAM#

什么是 Optimized-SC-F-LOAM？#

F-LOAM 的改进版本,并使用自适应阈值来进一步判断闭环检测结果并减少错误的闭环检测.此外,它还使用基于特征点的匹配来计算一对循环闭合帧点云之间的约束,并减少构建循环帧约束的时间消耗.

存储库信息#

原始仓库 link#

https://github.com/SlamCabbage/Optimized-SC-F-LOAM

必需的传感器#

LIDAR [VLP-16, HDL-32, HDL-64]

ROS 兼容性#

ROS 1

依赖#

ROS
PCL
GTSAM
Ceres Solver
为了可视化,此软件包使用 hector trajectory sever,您可以通过以下方式安装软件包

sudo apt-get install ros-noetic-hector-trajectory-server

构建并运行#

1) 建#

cd ~/catkin_ws/src
git clone https://github.com/SlamCabbage/Optimized-SC-F-LOAM.git
cd ..
catkin_make

2) 创建消息文件#

在此文件夹中,存储了 Ground Truth 信息、优化的姿势信息、F-LOAM 姿势信息和时间信息

mkdir -p ~/message/Scans

Change line 383 in the laserLoopOptimizationNode.cpp to your own "message" folder path

(不要忘记重新构建您的软件包)

3) 设置参数#

在 sc_f_loam_mapping.launch 上设置 LIDAR 主题和 LIDAR 属性

4) 运行#

source devel/setup.bash
roslaunch optimized_sc_f_loam optimized_sc_f_loam_mapping.launch

示例结果#

KITTI 序列 00 和序列 05 的结果#

KITTI 数据集上的轨迹比较#

KITTI 序列测试您可以从 KITTI 官网下载序列 00 和 05 数据集,并使用 kitti2bag 开源方法将其转换为 bag 文件.

00: 2011_10_03_drive_0027 000000 004540

05: 2011_09_30_drive_0018 000000 002760

见链接：https://github.com/ethz-asl/kitti_to_rosbag

确认#

Thanks for SC-A-LOAM(Scan context: Egocentric spatial descriptor for place recognition within 3d point cloud map) and F-LOAM(F-LOAM : 快速 LiDAR 里程计和地图绘制).

报价单#

@misc{https://doi.org/10.48550/arxiv.2204.04932,
  doi = {10.48550/ARXIV.2204.04932},

  url = {https://arxiv.org/abs/2204.04932},

  author = {Liao, Lizhou and Fu, Chunyun and Feng, Binbin and Su, Tian},

  keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences},

  title = {Optimized SC-F-LOAM: Optimized Fast LiDAR Odometry and Mapping Using Scan Context},

  publisher = {arXiv},

  year = {2022},

  copyright = {arXiv.org perpetual, non-exclusive license}
}