ROS 2 wrapper for the ZED SDK

pySLAM-D is a real-time SLAM algorithm for UAV aerial stitching. Includes additional features and refactored code inspired by BU's implementation https://github.com/armandok/pySLAM-D

RGBD-3DGS-SLAM is a monocular SLAM system leveraging 3D Gaussian Splatting (3DGS) for accurate point cloud and visual odometry estimation. By integrating neural networks, it estimates depth and camera intrinsics from RGB images alone, with optional support for additional camera information and depth maps.

"Visual-Inertial Dataset" (RA-L'21 with ICRA'21): it contains harsh motions for VO/VIO, like pure rotation or fast rotation with various motion types.

RGB-D Encoder SLAM for a Differential-Drive Robot in Dynamic Environments

A bunch of state estimation algorithms

visual odometry implementation w/ stereo cameras for localization in autonomous driving

visual (inertia) odometry of a drone with a monocular camera

An Illumination-Robust Point-Line Visual Odometry (IROS 2023)

Comparing the performance of the DeepVO network under different loss functions

An Invitation to 3D Vision: A Tutorial for Everyone

Deep Learning for Visual-Inertial Odometry

OAKD-series camera development demo

Implementation of the paper "Transformer-based model for monocular visual odometry: a video understanding approach".

COMO: Compact Mapping and Odometry

Underwater Dataset for Visual-Inertial Methods and data with transitioning between multiple refractive media.

Visual Odometry Pipeline using KITTI dataset

Notes and assignements of Self-Driving Cars Specialization from the University of Toronto on Coursera.

Building a full Visual SLAM pipeline to experiment with different techniques