Easily benchmark and develop SLAM algorithms in dockers.
-
Updated
Apr 10, 2024 - Shell
Easily benchmark and develop SLAM algorithms in dockers.
my implimentiona and implimentation of visual based SLAM algorithms
The docker environment for ORB-SLAM3 with ROS.
setup and working of rgbd slam on ros kinetic on ubuntu 16.04
Setup and working of orbslamv3 on ros kinetic on ubuntu 16.04
Custom integration of Neural Radiance Fields (NeRF) and Visual Simultaneous Localization and Mapping (VSLAM) based in NerfStudio.
Visual SLAM using an RBG Camera equipped on a Autonomous Vehicle
Modified version from raulmur/ORB_SLAM2 (commit f2e6f51 on Oct 11, 2017)
This is my collection of basis of Visual SLAM, which is aligned the book from Xiang Gao https://github.com/gaoxiang12/slambook-en
Python and Gazebo-ROS implementation of Image Quality Metric to evaluate the quality of image for robust robot vision.
OAKD-series camera development demo
Map Point Optimization in Keyframe-Based SLAM using Covisibility Graph and Information Fusion
Tools for the QueensCAMP dataset
Wheeled mobile robot
AR project based on "Monocular Visual-Inertial State Estimator on Mobile Phones"
Compendium of free robotic courses from universities around the world.
Codes for "Rao-Blackwellized particle smoothing for simultaneous localization and mapping"
Add a description, image, and links to the visual-slam topic page so that developers can more easily learn about it.
To associate your repository with the visual-slam topic, visit your repo's landing page and select "manage topics."