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

Step 1: Install Docker Engine

• Follow the official installation guide: Install Docker Engine.
• Apply the Linux post-installation configuration as non-root user: Linux post-installation steps for Docker Engine.

Step 2: NVIDIA Container Toolkit (optional)

If NVIDIA GPU is present.

• Install the toolkit: NVIDIA Container Toolkit.
• Configure Docker to use the NVIDIA runtime and restart the daemon:

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

Step 3: Clone the repository and build the development image

mkdir -p ~/ngps_ws/src
cd ~/ngps_ws/src
git clone git@github.com:snktshrma/ngps_flight.git
cd ~/ngps_ws/src/ngps_flight
docker build -f Dockerfile.dev -t vps-dev:latest .

For Docker only: Skip Step 4 and Step 5.

With NVIDIA GPU (requires Step 2):

docker run -it \
  --name vps-dev \
  --network host \
  --privileged \
  --ipc host \
  --gpus all \
  -v ~/ngps_ws:/home/dev/ngps_ws \
  -e DISPLAY=$DISPLAY \
  -v /tmp/.X11-unix:/tmp/.X11-unix \
  vps-dev:latest

Without NVIDIA GPU:

docker run -it \
  --name vps-dev \
  --network host \
  --privileged \
  --ipc host \
  -v ~/ngps_ws:/home/dev/ngps_ws \
  -e DISPLAY=$DISPLAY \
  -v /tmp/.X11-unix:/tmp/.X11-unix \
  vps-dev:latest

To start again:

docker start vps-dev
docker exec -it vps-dev /bin/bash

Step 4: Install Distrobox

For Ubuntu:

sudo apt install distrobox

export DBX_CONTAINER_MANAGER=docker
echo "export DBX_CONTAINER_MANAGER=docker" >> ~/.bashrc

Step 5: Create the Distrobox

• With NVIDIA GPU (requires Step 2):

distrobox create \
  --name vps-dev \
  --image vps-dev:latest \
  --additional-flags "--privileged --ipc=host --gpus all"

• Without GPU (no NVIDIA GPU or no toolkit):

distrobox create \
  --name vps-dev \
  --image vps-dev:latest \
  --additional-flags "--privileged --ipc=host"

Step 6: Enter and initialize the workspace

distrobox enter vps-dev

Inside the container:

bash ~/ngps_ws/src/ngps_flight/setup.sh
# When done,
source ~/.bashrc

Distrobox: The host user home directory is mounted; workspace paths such as ~/ngps_ws match the host, while binaries and libraries resolve from the container image.

Step 7: Verify the simulation stack

ros2 launch ardupilot_gz_bringup iris_runway.launch.py

• Expected result: ArduPilot DDS and Gazebo Harmonic start with the runway simulation.

Removing or reconnecting

Distrobox::

distrobox stop vps-dev
distrobox rm vps-dev

Docker:

docker stop vps-dev
docker rm vps-dev

---

Package-level setup

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

Special mentions

Ofcourse, ChatGPT :)

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.