“Nordluft’s core innovation is a high-capacity drone-based spreader system, designed for the needs of forestry. A central part of this system is the control system that coordinates a swarm of drones. The project effort has meant that Nordluft has been able to rebuild the foundation of this system to increase efficiency, reduce delays in the system, and make the architecture cleaner and more transparent. This is very important to enable future development efforts, but also provides clear improvements at the current stage. The result will be shown to the industry in the spring of 2026 when an air permit finally enables demonstrations of drone-based forest fertilization with major benefits for forestry productivity and carbon sequestration”, says Elof Winroth, Founder, Nordluft Automation.
Challenges
Nordluft specializes in drone-based spreading systems for forestry and agriculture, using a fleet of heavy-lift drones autonomously controlled by a centralized system called NGC (Nordluft Ground Control). While a prototype of NGC was operational, it had significant limitations in robustness, user-friendliness, and performance. These shortcomings hindered practical deployment and scalability.
The challenge was to upgrade NGC to improve system reliability, simplify the user interface, and optimize performance for real-world operations. This included restructuring the architecture to eliminate unnecessary onboard components and streamline mission execution for drone swarms.
Solutions
Aero EDIH supported Nordluft through Oskar Enoksson AB. The project began in late summer 2024 and involved full-time development and testing at Barkarby airfield.
One critical task was removing the Raspberry Pi units (small single-board computer) previously installed in each drone. These handled the “vehicle handler” function, which was migrated to the ground station software running on a centralized computer. This architectural change simplified hardware requirements and improved maintainability.
Additional improvements included changing the drone operating mode from “guided” to “auto,” enabling more autonomous behavior and reducing complexity in mission control. The upgraded system was validated using scaled-down drones in real-world conditions.
Results and Benefits
The project successfully delivered a more robust and streamlined version of NGC, eliminating redundant hardware and consolidating critical functions into the ground station software. This upgrade enhances system reliability, reduces maintenance overhead, and improves operational efficiency for Nordluft’s drone swarms.
The changes also pave the way for future optimizations, such as dynamic altitude adjustments based on terrain profiles and integrated battery swap management to minimize downtime. These improvements will enable Nordluft to scale its solution for forestry and agricultural applications, supporting sustainable and efficient resource management.
Perceived social/economic impact
By upgrading its ground control system, Nordluft strengthens its ability to deliver autonomous drone services for forestry and agriculture. These improvements support digital transformation in rural industries, reduce manual labor, and enhance operational efficiency. The result is a more sustainable approach to resource management, contributing to economic growth and environmental stewardship.
Lessons learned
Focus on simplifying system architecture early to reduce complexity and improve reliability. Validate changes through real-world testing to ensure practical usability. Engage in iterative development to address both technical and operational needs.
Avoid relying on distributed hardware components when centralized solutions can deliver better maintainability. Do not postpone user interface improvements – operator experience is critical for efficiency and safety.
”The project significantly enhanced the robustness and performance of the Nordluft Ground Control (NGC) system by centralizing vehicle handling and removing hardware dependencies within the drones”, says Per Bröms, Innovation Lead, Aero EDIH.
