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backtobackswe

Code Examples For Back To Back SWE Lessons

cartographer_installation

shell script for installtion of cartographer_ros

cartographer_superbuild

feature-based-lidar-slam-in-python

This is a completed version of Claus Brenner's open course in YouTube.

git_test

graphslam

graphslam

hit

learnslam

SLAM研习社

loam_livox

A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR

pcl

Point Cloud Library (PCL)

peac

PEAC(Plane Extraction using Agglomerative Clustering) is a fast plane segmentation algorithm for organized point cloud. This is a fork of peac (http://www.merl.com/research/license)

pyukf

Unscented kalman filter (UKF) library in python that supports multiple measurement updates

slam

Python files for SLAM course by Claus Brenner

slam-1

SLAM programms

slam-2

learning SLAM,curse,paper and others

tams-planar-surface-based-perception

3D perception code developed at TAMS (http://tams.informatik.uni-hamburg.de/) by Junhao Xiao and others, including point cloud plane segmentation, planar segment area calculation, scan registration based on planar segments, etc.

vo-slam-review

SLAM is mainly divided into two parts: the front end and the back end. The front end is the visual odometer (VO), which roughly estimates the motion of the camera based on the information of adjacent images and provides a good initial value for the back end.The implementation methods of VO can be divided into two categories according to whether features are extracted or not: feature point-based methods, and direct methods without feature points. VO based on feature points is stable and insensitive to illumination and dynamic objects

xv11lidar_stm32f429

Neato XV-11 LIDAR connected to an STM32F429IDISCOVERY board for 360-degree range scanning and measurement