This repository is an example use-case ofScan Context, which is a fast and robust LiDAR place recognition method. For more details for each algorithm please refer to Scan Contexthttps://github.com/irapkaist/scancontext LIO-SAMhttps://github.com/TixiaoShan/LIO-SAM You can also use the LiDAR...
该开源库是在A-LOAM的基础上在增加了回环检测和位姿图优化模块(名为SC-PGO) 该库也在FAST-LIO2激光里程计中集成了。其代码位于 : https://github.com/gisbi-kim/SC-A-LOAM https://github.com/gisbi-kim/FAST_LIO_SLAM 主要内容及贡献 实时激光雷达SLAM集成了A-LOAM和ScanContext。 A-LOAM用于里程计模块...
A Scan Context integration for LIO-SAM, namedSC-LIO-SAM (link), is also released. Real-time LiDAR SLAM: Scan Context (18 IROS) + LeGO-LOAM (18 IROS) This repository is an example use-case ofScan Context C++, the LiDAR place recognition method, for LiDAR SLAM applications. For more de...
LIO-SAMhttps://github.com/TixiaoShan/LIO-SAM You can also use the LiDAR-only version of this project, namedSC-LeGO-LOAM. Scan Context: A fast and robust place recognition Light-weight: a single header and cpp file named "Scancontext.h" and "Scancontext.cpp" ...
In this example, Scan Context is integrated with FAST-LIO (https://github.com/hku-mars/FAST_LIO). Note: No additional integration effort is required. A user just run seperately FAST-LIO node and SC-A-LOAM's posegraphoptimization.cpp node!
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However, low complex linear interpolation technique can be chosen for highly rated pilot signal transmission cases or when optical channel varies slowly over the time.Omer NarmanliogluBugra TuranRefik Caglar KizilirmakSinem Coleri ErgenMurat Uysal会议论文...
Fast: The loop detector runs at 10-15Hz (for 20 x 60 size, 10 candidates) Examples Video 1: DCC (MulRan dataset) Video 2: Riverside (MulRan dataset) Video 3: KAIST (MulRan dataset) Scan Context integration For implementation details, see themapOptmization.cpp; all other files are same...