orbslam-map-saving-extension
A ROS package extension for ORB-SLAM2 that enables saving and loading ORB feature maps for closed-circuit visual localization of autonomous vehicles.
What is orbslam-map-saving-extension?
ORB-SLAM map saving extension is a ROS package that adds map persistence functionality to ORB-SLAM2, enabling autonomous vehicles to save ORB feature maps to disk and reload them for future localization runs. It solves the problem of maintaining accurate localization at high speeds in repetitive environments like racing circuits by separating the mapping phase (done once at low speed) from the localization phase (performed repeatedly at high speed).
Robotics researchers and engineers working on autonomous vehicle localization, particularly those using ORB-SLAM2 in ROS environments for closed-circuit applications like autonomous racing or repetitive industrial routes.
Developers choose this extension because it provides a simple yet effective way to persist ORB-SLAM2 maps, enabling more reliable high-speed localization than real-time SLAM while maintaining compatibility with existing ORB-SLAM2 workflows and the KITTI dataset ecosystem.
Overview
This project extends ORB-SLAM2 with map persistence capabilities, allowing autonomous vehicles to save ORB feature maps to disk and reload them for subsequent localization runs. It's designed specifically for closed-circuit racing scenarios where high-speed localization accuracy is critical. By separating mapping (done at low speeds) from localization (performed at high speeds), it improves positioning reliability compared to full SLAM approaches.
Key Features
- Map Persistence — Saves ORB feature maps to disk as binary files for future reuse
- Map-Based Localization — Loads pre-built maps to localize within known environments at higher speeds
- ROS Integration — Provides ORB-SLAM2 functionality as a ROS package with topic broadcasts for camera poses, map points, and tracking states
- KITTI Dataset Compatibility — Includes example workflows using the KITTI autonomous driving dataset
- Trajectory Visualization — Comes with tools to compare mapping and localization trajectories
- Feature Matching Visualization — Enables real-time visualization of ORB feature matching during SLAM/localization
Philosophy
The extension follows a practical engineering approach: decouple mapping from localization to achieve better accuracy at high speeds in repetitive environments, prioritizing reliability over real-time map building in closed-circuit scenarios.
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