GhostPilot: Open-Source GPS-Denied Drone Navigation using Visual SLAM and AI

GhostPilot: GPS-Denied Drone Navigation with Visual SLAM and Agentic AI

Aman Sachan has developed GhostPilot, an open-source navigation stack for autonomous drones operating in GPS-denied environments. GPS jamming in conflict zones has historically neutralized up to 85% of drone squadrons, necessitating alternative localization methods. The system utilizes visual-inertial SLAM and agentic AI to maintain 6DOF pose estimation without external satellite signals.

Why This Matters

The technical reality of drone deployment is that GPS signals are frequently unavailable in urban canyons, forests, and indoor environments, or are intentionally jammed in military contexts. While military-grade solutions exist, they typically cost $50,000 or more, and academic alternatives are often unmaintained and difficult to implement. GhostPilot addresses this by providing a ROS2-native, edge-native alternative that runs on accessible hardware like the NVIDIA Jetson Orin or Raspberry Pi 5, democratizing high-end navigation capabilities.

Key Insights

• GPS jamming in Ukraine rendered 85% of some drone squadrons ineffective, proving the vulnerability of satellite-dependent flight.
• Visual-Inertial SLAM (VINS-Mono) utilizes camera and IMU fusion for 6DOF pose estimation without requiring GPS connectivity.
• Agentic AI mission planning allows for natural language command processing, translating instructions like ‘Inspect the roof’ into executable navigation goals.
• Integration with Nav2 provides industry-standard path planning and obstacle avoidance for edge-native hardware.
• The GhostPilot stack is designed for the NVIDIA Jetson Orin and Raspberry Pi 5, ensuring high-performance local compute without cloud dependencies.

Working Examples

GhostPilot quick start setup and simulation launch commands.

git clone https://github.com/amsach/GhostPilot.git
cd GhostPilot
./scripts/setup_jetson.sh
ros2 launch ghostpilot_gazebo indoor_warehouse.launch.py
ros2 run ghostpilot_agent mission_parser_node

Practical Applications

• Indoor Warehouse Navigation: Using the agentic layer to command drones to check specific rooms for occupants in GPS-denied environments. Pitfall: Attempting to use proprietary closed-source stacks which limit hardware customization.
• Urban Canyon Reconnaissance: Navigating high-density urban environments where GPS signals are blocked or reflected by buildings. Pitfall: Relying on pre-programmed waypoints that cannot adapt to real-time obstacle detection.

References:

• https://dev.to/aman_sachan_126d19c4a2773/ghostpilot-gps-denied-drone-navigation-with-visual-slam-and-agentic-ai-416l