NGPS: Next-Generation Positioning System

Next-Generation Positioning System (NGPS) for high-altitude drone navigation without GPS.

Description

This codebase implements a visual geo-localization system for drones that matches down-facing camera images against satellite reference images using deep learning-based feature matching. The system provides absolute position estimates to correct drift in Visual-Inertial Odometry (VIO) systems.

Main Components

• ap_ngps_ros2: ROS2 node that performs visual geo-localization by matching camera images to satellite reference images using LightGlue/SuperPoint deep learning features. Runs at 1-2 Hz.

• ap_ukf: Unscented Kalman Filter that fuses multiple sensor inputs:

  • NGPS absolute position (1-2 Hz)
  • VIO relative pose (10-20 Hz)
  • IMU data (high frequency) Outputs fused odometry at 10-20 Hz for flight control.

• ap_vips: Visual-Inertial Odometry system that provides high-frequency relative pose estimates optimized for high-altitude flight.

How It Works

1. NGPS module matches real-time camera frames to a georeferenced satellite reference image
2. Provides absolute position estimates at low frequency (1-2 Hz)
3. UKF fuses NGPS absolute positions with high-frequency VIO estimates
4. Fused output sent to ArduPilot's EKF for final state estimation

Demo

Algorithm Demonstration Video

Related Articles & Blogs

• GSoC 2024: High Altitude Non-GPS Navigation - Initial GSoC project summary
• Transformer & Optimization Based High Altitude GPS-Denied Fusion - Updated implementation and architecture details

Related Projects

• ap_nongps - Earlier prototype implementation with SIFT-based feature matching and optical flow methods

TODO

• Add a fallback VO pipeline
• Add global optimisation for fusion
• Update AP to accept position and odometry as separate sources to be fused internally
• Add support for multiple reference images
• Optimize feature matching for faster performance
• Add calibration tools and documentation
• Improve error handling and recovery
• Add more unit tests
• Document configuration parameters
• Add example launch files for different scenarios
• Performance profiling and optimization
• Support for different camera models

Installation

See individual package READMEs:

• ap_ngps_ros2/README.md
• ap_ukf/README.md
• ap_vips/README.md

Documentation

• Changelog - Project history and version timeline
• Camera-IMU Calibration - Google Docs
• Non-GPS Navigation Setup - Google Docs

Acknowledgements

A huge shoutout to my partner in disguise, ChatGPT, for generating tests and helping with packaging this codebase.

Safety & Ethical Considerations

IMPORTANT DISCLAIMER: This software is provided for research and educational applications only. The developers and contributors of this project doesn't promote and are not responsible for any misuse.

License

See LICENSE file.