cuVSLAM: CUDA-Accelerated Visual Odometry and Mapping

LRAE: Large-Region-Aware Safe and Fast Autonomous Exploration of Ground Robots for Uneven Terrains, RA-L, 2024

A benchmark platform for robot grasping detection, integrating awesome projects and classic grasp algorithms.

[ICRA'24] A localization system based on Block Maps (BMs) to reduce the computational load caused by maintaining large-scale maps

[ICRA2023] Implementation of Visual Language Maps for Robot Navigation

An intuitive approach for 3D Occupancy Detection

Nano-GICP as a module from the official github repo: [IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.

D-Map provides an efficient occupancy mapping approach for high-resolution LiDAR sensors.

《自动驾驶中的SLAM技术》对应开源代码

FASTER-LIO-SAM: A SLAM system based on iVox and GTSAM.

The tight integration of FAST-LIO with Radius-Search-based loop closure module.

A simplified implementation of FAST_LIO (with Chinese note)

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

导航“前端”，将定位后的三维点云实时或离线三维到二维栅格化，并计算代价生成代价地图。

LiDAR-inertial SLAM: Scan Context + LIO-SAM

This repo is modified based on LIO_SAM, which remove the feature extraction module and makes it easier to adapt your sensor.

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels

Two ROS interfaces Mono_inertial and Stereo_inertial were added to the ORB-SLAM3 . Modified the loading vocabulary in a faster binary way.

cartographer work space with detailed comments

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

A Lidar-Inertial State Estimator for Robust and Efficient Navigation based on iterated error-state Kalman filter

Multi-Sensor Fusion (GNSS, IMU, Camera) 多源多传感器融合定位 GPS/INS组合导航 PPP/INS紧组合

CVPR 2020 论文开源项目合集

Robust and Efficient Visual-Inertial Odometry with Multi-plane Priors