Objectives of the service
Hospitals and laboratories in the Munich/Ingolstadt region face significant challenges in the transport of time-critical medical goods such as lab samples and pharmaceuticals. Current road-based transport is slow, unreliable due to traffic and costly.
SURGEON addresses these challenges by developing a fully autonomous drone delivery service engineered for the healthcare sector. The system enables direct delivery from central pharmacies and laboratories to hospital windows, requiring no ground infrastructure investment from customers and no dedicated pilot per drone.
The core objective of this demonstration project is to validate a redundant, GNSS-independent navigation system based on semantic satellite Earth Observation data combined with visual inertial odometry. This eliminates the primary single point of failure in current drone technology, GNSS signal dependency, and enables scalable, safe Beyond Visual Line of Sight operations.
The project is executed by Maple Aviation GmbH together with Fraunhofer IVI as software developer and Klinikum Rechts der Isar as pilot user and customer, with the goal of entering commercial operations in Q4 2027.
Users and their needs
The primary user communities are hospitals, pathology laboratories, and central pharmacies in the German healthcare sector, initially focused on the Munich/Ingolstadt region. Key user needs include:
Speed: Lab samples must reach pathology within minutes to avoid delays in ongoing surgeries.
Reliability: Road-based transport is frequently delayed due to traffic, leading to cancelled or repeated procedures.
Simplicity: No infrastructure investment or specialist training should be required from hospital staff, only packing and unpacking of transport boxes.
Safety: Medical goods must be transported securely, with no spoilage or loss.
Maple Aviation has established partnerships with a broad network of hospitals and laboratories across Bavaria, including LMU Kliniken, Klinikum Ingolstadt, Klinikum Rechts der Isar, Pathology Ingolstadt, Pfaffenhofen Ilmtalklinik, Mainburg Krankenhaus, and Schrobenhausen Kreiskrankenhaus, among others. All targeted institutions operate surgery departments and do not run their own laboratory, making drone-based sample transport a high-value, high-frequency use case.
Service/ system concept
The SURGEON system consists of an autonomous drone equipped with both a GNSS navigation system and an onboard camera system, as well as a window adapter at each pickup and delivery location at the respective hospital or laboratory.
The core focus of the SURGEON project is to enhance the reliability of this drone delivery service through a GNSS-denied navigation capability, ensuring safe and continued operation even in the event of a GPS signal loss.
Pre-processed semantic Earth Observation data sourced via Google Earth Pro is prepared in the cloud prior to each flight and loaded onto the drone before departure. During flight, the onboard AI matches live camera images against this semantic map using a novel pose retrieval framework, providing continuous position estimation independent of GNSS. Classical visual inertial odometry ensures short-term stability, while GNSS serves as an additional redundant input where available. The fusion of all three methods creates a navigation system with no single point of failure.
The drone flies at up to 90 km/h, the regulatory maximum, and delivers directly to a window docking adapter, eliminating the need for landing pads or staff involvement during flight. One remote operator can supervise up to 30 drones simultaneously, enabling cost-competitive and scalable operations.
Space Added Value
The SURGEON service depends fundamentally on satellite Earth Observation data as its primary enabler for GNSS-independent navigation. Semantic satellite imagery sourced from Google Earth Pro is pre-processed to create detailed semantic maps of the flight corridors. These maps allow the drone to recognize and match ground features such as roads, buildings, and vegetation across varying seasons and weather conditions, providing a reliable global position reference even when GNSS is unavailable or unreliable.
This approach offers decisive advantages over the main alternatives: military-grade Inertial Measurement Units are expensive, heavy, export-restricted, and suffer from cumulative drift over time. Optical flow sensors are limited to altitudes below 50 meters and cannot provide global positioning. Neither alternative is viable for commercial urban drone operations.
By combining satellite Earth Observation data with onboard AI and visual inertial odometry, SURGEON achieves a navigation solution that is robust against seasonal changes, weather variability, and urban GNSS interference, conditions that are common in real-world healthcare logistics. The use of space assets is therefore not supplementary but central to the business model: without reliable GNSS-denied navigation, the required drone-to-operator ratio of 30:1 cannot be achieved, and the service becomes economically unviable.
Current Status
The SURGEON demonstration project is currently in its initial phase. Maple Aviation GmbH has completed a hardware prototype of the ducted fan propulsion system within a prior ESA BIC Bavaria activity. Onboard AI development for autonomous landing is underway in collaboration with Technische Hochschule Ingolstadt and Fraunhofer IVI, with active flight testing ongoing.
A broad network of hospital and laboratory partners across Bavaria has been established, including the first confirmed customers beyond the region in the broader German market. The consortium has passed the technical audit by the German Luftfahrtbundesamt for MOC-SORA BVLOS corridor operations.
Development of the semantic GNSS-denied navigation system, the core technology of this project, is now commencing under the ESA demonstration contract.
