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verified publisher icon qdLMF
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A CUDA reimplementation of the line/plane odometry of LIO-SAM. A point cloud hash map (inspired by iVox of Faster-LIO) on GPU is used to accelerate 5-neighbour KNN search.

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Have you done an accuracy comparison between original and your version?

1 comment

In any case, nice work. I personally optimized LIO-SAM with nanoflann_pcl and replaces all instances of radius search with knn search to reach a 2x speedup. GPU based knn search...

juliangaal avatar juliangaal

mapping drift when using the dataset provided by lio-sam

9 comment

Thans for your great work. While the robot will drift immediately when using the dataset "Campus dataset (small)" like this. What should I modify the project. ![mapping_drift](https://github.com/qdLMF/LIO-SAM-GPU-ScanToMapOpt/assets/33504360/578cca0c-b645-4999-91ec-960ca83d2f64)

xiaoxueshengyao avatar xiaoxueshengyao

[pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [pcl::VoxelGrid::applyFilter] Invalid filter field name. Index is -1. [ WARN] [1721892902.904266764]: Not enough features! Only 0 edge and 0 planar features available.

I encountered an error while running the GPU version of LIO-SAM, but the original version works fine. Does anyone know how to resolve this issue? [pcl::VoxelGrid::applyFilter] Invalid filter field name....

widmer2001 avatar widmer2001

Is it possible to run with CUDA 10.2?

Is it possible to run this repository with CUDA 10.2? I have tried it but I only get an error message: `CMake Error at /usr/share/cmake-3.25/Modules/FindPackageHandleStandardArgs.cmake:230 (message): Could NOT find CUDA...

GXrobot avatar GXrobot

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verified publisher icon qdLMF

Metadata

A CUDA reimplementation of the line/plane odometry of LIO-SAM. A point cloud hash map (inspired by iVox of Faster-LIO) on GPU is used to accelerate 5-neighbour KNN search.

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