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dlio-based-data-production's Introduction

使用DLIO制作EgoNN的数据集

基于ROS2的DLIO,点云pcd文件输出到workspace下的bin文件夹中,目前是绝对路径,复现请对odom.cc与odom.h进行pcd_path进行review. 位姿同理,输出到workspace下的pose.yaml,修改后缀可得到txt.相应的变量是pose_yaml_file.

DLIO与FAST-LIO青龙仓对比

缺少回环的FastLio无法完成地面一致的闭合

drawing

drawing

缺少回环的dlio虽然地面看起来一致,但是风扇叶片的细节看出来全局一致性还是和LIO-SAM差点

drawing

drawing

drawing

LIO-SAM叶片一致:

drawing

数据集下载

链接: https://pan.baidu.com/s/11qyWsf89mOseqhwGmAmdkQ 提取码: 2rs1 雷达频率20hz 点云已作畸变去除 为车体base_link下 位姿为base_link到map系下 点云格式:

drawing

编译与注明

Direct LiDAR-Inertial Odometry: Lightweight LIO with Continuous-Time Motion Correction(https://github.com/vectr-ucla/direct_lidar_inertial_odometry)

DLIO is a new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction. It features several algorithmic improvements over its predecessor, DLO, and was presented at the IEEE International Conference on Robotics and Automation (ICRA) in London, UK in 2023.

dlio-based-data-production's People

Contributors

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