945 Open source projects that are alternatives of or similar to Lego Loam

Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.

Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

Interactive Map Correction for 3D Graph SLAM

UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes

LiDAR SLAM: Scan Context + LeGO-LOAM

ROS wrappers for SLAM algorithms in MRPT

Python package for the evaluation of odometry and SLAM

Open-Source LiDAR Time Synchronization System by Mimicking GPS-clock

ROS driver for all of MicroStrain's current G and C series products. To learn more visit

Use LiDAR to map the static world

UrbanNav: an Open-Sourcing Localization Data Collected in Asian Urban Canyons, Including Tokyo and Hong Kong

loam code noted in Chinese（loam中文注解版）

ROS wrapper for Kimera-VIO

Poisson Surface Reconstruction for LiDAR Odometry and Mapping

A Modular Framework for LiDAR-based Lifelong Mapping

3D LIDAR-based Graph SLAM

An open source autonomous driving research platform for Active SLAM & Multisensor Data Fusion

🚀 SLAM for autonomous planetary rovers with global localization

ROS Error-State Kalman Filter based on PX4/ecl. Performs GPS/Magnetometer/Vision Pose/Optical Flow/RangeFinder fusion with IMU

This ROS kinectic workspace src folder, which was created on Ubuntu 16.04. Here I worked on ROS1 projects like 2d & 3D SLAM, Motion Planning, SWARM of drone, RL based drone, Surveilling Robot etc.

A Multi-sensor Fusion Odometry via Smoothing and Mapping.

open source slam system notes

My small SLAM simulator to study "SLAM for dummies"

2019 DGIST DPoom project under UGRP : SBC and RGB-D camera based full autonomous driving system for mobile robot with indoor SLAM

ROS Catkin package to track people using octree and cluster extraction

😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.

ROS and V-REP for Robot Mapping and Localization

ROS机器人操作系统 学习（写于2020年夏）

ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM

SLAM Kit

Ros nodes for single TeraRanger sensors

No description or website provided.

Graph SLAM solver in Python

Official page of Patchwork (RA-L'21 w/ IROS'21)

Android implementation of "Fusion of inertial and visual measurements for rgb-d slam on mobile devices"

Trifo Ironsides SDK

Visualize Data From Stray Scanner https://keke.dev/blog/2021/03/10/Stray-Scanner.html

VINS-Mono中文注释

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

LiDAR SLAM = FAST-LIO + Scan Context

ROS driver for VN-100 of VectorNav Technologies

MOLA module: Front-end for point-cloud sensors based on generic ICP algorithms. LiDAR odometry and loop closure.

OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)

A ROS implementation of ORB_SLAM2

A collection of deep learning based localization models

(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping

Real time semantic slam in ROS with a hand held RGB-D camera

Real-time 3D localization using a (velodyne) 3D LIDAR

A driving dataset for the development and validation of fused pose estimators and mapping algorithms

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

ROS wrapper for the ZED SDK

Point cloud registration pipeline for robot localization and 3D perception

Robot-centric elevation mapping for rough terrain navigation

Visual-Inertial-Semantic-MApping Dataset and tools

ROS packages for Turtlebot3

🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.

The ROS Package of Mask R-CNN for Object Detection and Segmentation

ROS package to find a rigid-body transformation between a LiDAR and a camera for "LiDAR-Camera Calibration using 3D-3D Point correspondences"

Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.