BSD 2-Clause "Simplified" License

项目介绍

koide3/ndt_omp 是一个托管在 GitHub 上的开源项目,主要使用 C++ 编写,采用 BSD 2-Clause "Simplified" License 许可证,目前获得 861 个 Star、275 次 Fork。

仓库全名
koide3/ndt_omp
开源许可证
BSD 2-Clause "Simplified" License
Star 数
861
Fork 数
275
未关闭 Issue
28

README 摘要

ndtomp This package provides an OpenMP-boosted Normal Distributions Transform (and GICP) algorithm derived from pcl. The NDT algorithm is modified to be SSE-friendly and multi-threaded. It can run up to 10 times faster than its original version in pcl. For using this package in non-ROS1 projects (ROS2 or without ROS), see forked repositories: dfki-ric/pclomp tier4/ndtomp. Benchmark (on Core i7-6700K) Several methods…

完整内容见 GitHub 原始 README 或本页 。

常见问题

ndt_omp 用什么语言开发?

主要使用 C++ 编写,采用 BSD 2-Clause "Simplified" License 许可证,目前有 861 个 Star。

ndt_omp 可以免费商用吗?

仓库采用 BSD 2-Clause "Simplified" License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 ndt_omp 的源码?

可以直接克隆仓库:git clone https://github.com/koide3/ndt_omp.git,默认分支为 master;安装与运行步骤见仓库 README。

ndt_omp 最近还在维护吗?

仓库最近一次更新为 2024年8月31日,当前有 28 个未关闭 Issue;Star 数为 861,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

Multi-threaded and SSE friendly NDT algorithm

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
1430
价值分
599
活跃状态
活跃

语言占比

C++
CMake
Dockerfile

README

ndt_omp

This package provides an OpenMP-boosted Normal Distributions Transform (and GICP) algorithm derived from pcl. The NDT algorithm is modified to be SSE-friendly and multi-threaded. It can run up to 10 times faster than its original version in pcl.

For using this package in non-ROS1 projects (ROS2 or without ROS), see forked repositories: dfki-ric/pclomp tier4/ndt_omp.

Build

Benchmark (on Core i7-6700K)

$ roscd ndt_omp/data
$ rosrun ndt_omp align 251370668.pcd 251371071.pcd
--- pcl::NDT ---
single : 282.222[msec]
10times: 2921.92[msec]
fitness: 0.213937

--- pclomp::NDT (KDTREE, 1 threads) ---
single : 207.697[msec]
10times: 2059.19[msec]
fitness: 0.213937

--- pclomp::NDT (DIRECT7, 1 threads) ---
single : 139.433[msec]
10times: 1356.79[msec]
fitness: 0.214205

--- pclomp::NDT (DIRECT1, 1 threads) ---
single : 34.6418[msec]
10times: 317.03[msec]
fitness: 0.208511

--- pclomp::NDT (KDTREE, 8 threads) ---
single : 54.9903[msec]
10times: 500.51[msec]
fitness: 0.213937

--- pclomp::NDT (DIRECT7, 8 threads) ---
single : 63.1442[msec]
10times: 343.336[msec]
fitness: 0.214205

--- pclomp::NDT (DIRECT1, 8 threads) ---
single : 17.2353[msec]
10times: 100.025[msec]
fitness: 0.208511

Several methods for neighbor voxel search are implemented. If you select pclomp::KDTREE, results will be completely the same as that of the original pcl::NDT. We recommend using pclomp::DIRECT7 which is faster and stable. If you need extremely fast registration, choose pclomp::DIRECT1, but it might be a bit unstable.


Red: target, Green: source, Blue: aligned

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