代码拉取完成,页面将自动刷新
Scancontext.h
. For details see the file mapOptmization.cpp
.Scancontext.h
) can be easily integrated with any other key-frame-based odometry (e.g., wheel odometry or ICP-based odometry).makeAndSaveScancontextAndKeys
and detectLoopClosureID
.mapOptmization.cpp
; all other files are same as the original LeGO-LOAM.mapOptmization.cpp
for details. (the original LeGO-LOAM used non-robust kernel). We found that Cauchy is emprically enough.mapOptmization.cpp
for details. SC is good for correcting large drifts and RS is good for fine-stitching.SC-LeGO-LOAM
under user catkin work spacecd ~/catkin_ws/src
git clone https://github.com/irapkaist/SC-LeGO-LOAM.git
cd ..
catkin_make
source devel/setup.bash
roslaunch lego_loam run.launch
@INPROCEEDINGS { gkim-2018-iros,
author = {Kim, Giseop and Kim, Ayoung},
title = { Scan Context: Egocentric Spatial Descriptor for Place Recognition within {3D} Point Cloud Map },
booktitle = { Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems },
year = { 2018 },
month = { Oct. },
address = { Madrid }
}
and
@inproceedings{legoloam2018,
title={LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain},
author={Shan, Tixiao and Englot, Brendan},
booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={4758-4765},
year={2018},
organization={IEEE}
}
paulgkim@kaist.ac.kr
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