Donecle aims to revolutionize aircraft maintenance with automated drone inspections. With a growing air traffic market and labor shortages, optimizing maintenance efficiency is crucial. Our project, "I3DM," seeks to address these labor shortages, by optimizing maintenance efficiency and enhancing safety. Donecle's Iris 3D Mapping drone, with its fully automated flight and precise damage detection, reduces inspection times from hours to minutes, enabling faster aircraft turnaround and reduced AOG costs. The project's objectives are threefold: 1) Technological Innovation: Further develop and validate the Iris drone's automated flight, obstacle avoidance, and precise damage detection and surface deformations such as dents, achieving TRL 9; 2) Regulatory Compliance: Obtain necessary approvals and certifications for commercial deployment, addressing potential delays in regulatory approvals; 3) Market Penetration: Expand geographically, targeting key aviation markets, and ensuring worldwide adoption of the solution by airlines, MROs, and manufacturers. We will achieve these objectives through extensive testing, collaboration with industry stakeholders, and strategic market expansion. The final solution, including drone, software, and data hosting, optimizes maintenance processes, improves safety, and provides actionable data insights. The solution can be extended to other applications, such as ships and wind turbines inspection. Our strong established IP, with patents already filed in several countries, and our experienced team ensure the project's success. The project's estimated costs are €3.5M, with a requested grant of €2.5M. The EIC Accelerator funding will be crucial for Donecle to bring this innovative solution to market, outcompete rivals, and drive industry-wide adoption.

The main objective of AERIAL-CORE is the development of core technology modules and an integrated aerial cognitive robotic system that will have unprecedented capabilities on the operational range and safety in the interaction with people, or Aerial Co-Workers (ACW), for applications such as the inspection and maintenance of large infrastructures. The project will integrate aerial robots with different characteristics to meet the requirements of: (1) Long range (several kilometres) and local very accurate (subcentimetre) inspection of the infrastructure capability; (2) Maintenance activities based on aerial manipulation involving force interactions; and (3) Aerial co-working safely and efficiently helping human workers in inspection and maintenance. AERIAL-CORE technology modules will be based on Cognitive Mechatronics and apply cognitive capabilities to aerial morphing in order to combine long range endurance and hovering for local observations, manipulation involving force interactions, and co-working with humans. The project will develop: (1) Cognitive functionalities for aerial robots including perception based on novel sensors, such as event cameras, and data fusion techniques, learning, reactivity, fast on-line planning, and teaming; (2) Aerial platforms with morphing capabilities, to save energy in long range flights and perform a very accurate inspection; (3) Cognitive aerial manipulation capabilities, including manipulation while flying, while holding with one limb, and while hanging or perching to improve accuracy and develop greater forces; (4) Cognitive safe aerial robotic co-workers capable of physical interaction with people; and (5) Integrated aerial robotic system for the inspection and maintenance of large infrastructures. The system will be demonstrated in electrical power system inspection and maintenance, which is an application with a huge economic impact that also has implications in the safety of workers and in wildlife conservation.