pySLAM是一个混合了Python和C++语言的视觉SLAM解决方案,适用于单目、立体以及RGB-D类型的摄像头。它提供了多种现代局部和全局特征提取方法、多种循环闭合策略、体积重建模块、集成式的深度预测模型,以及语义分割功能,从而帮助更好地理解场景结构。
loop-closure 开源项目推荐(74 个)
loop-closure 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 74 个仓库用于点云地图制作、基准测试和 Autoware 兼容地图工作流的 ROS 2 LiDAR SLAM。
A 3D point cloud descriptor for place recognition
The tight integration of FAST-LIO with Radius-Search-based loop closure module.
Python对SLAM算法Stereo-PTAM的实现
slamplay is a collection of powerful tools to start playing and experimenting with SLAM in C++
ROS 2 package of tightly-coupled lidar inertial ndt/gicp slam
ICRA 2021 - Robust Place Recognition using an Imaging Lidar
[3DV 2025, Oral] LoopSplat: Loop Closure by Registering 3D Gaussian Splats
Fisheye version of VINS-Fusion
A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on Quatro and Nano-GICP
A Map-based localization implementation combining FAST-LIO2 as an odometry with Quatro + Nano-GICP as a map matching method
graph-theoretic framework for robust pairwise data association
SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation
[ICRA'23] Official code repo for "Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose Estimation"
Convolutional Autoencoder for Loop Closure
A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on ScanContext, Quatro, and Nano-GICP
将superpoint、lightglue、MixVPR合并到VINS-FUSION中,用TensorRT实现环路闭合
SLAM package using NDT registration library of Autoware with loop-closure detection (odometry based) referenced from lego_loam.
Graph-based image sequences matching for the visual place recognition in changing environments.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/loop-closure。
- 该话题在 GitHub 上共有 74 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 1.1 万 Star,覆盖 2 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。