The Project started on June 1, 2020. In the first 18 months, the drone system specifications and architecture have been defined and a preliminary description and analysis of the two use-cases (bridges and railways inspections) to verify and validate the platform has been developed, together with a list of selected test sites where the defined use-cases may be executed.
Preparation of the business model for the Drones4Safety (D4S) project in order to show the project’s feasibility from a technical and economic/financial sides.
The design of the system architecture follows top-down design methodologies with well-defined system interfaces to assure a flexible system design and seamless integration between the subsystem components of the D4S system. In addition, the architecture is designed to include multiple drones for swarming operations. The architecture assures the safety of the platform by separating the drone control system into two parts, high and low-level flight controls to guarantee a stable autonomous system design.
The research in drone autonomous navigation and grasping on overhead cables have been started by a global survey on lightweight sensors for cable detections with deep evaluations of the sensor findings. A flexible drone system has been developed using advanced heterogeneous chips (MPSoC) and sensors.
The research in AC and DC recharging started with a deep understanding of the environment in which the drone will be operating, which is followed by a design and a development of lightweight harvesting mechanisms for recharging from powerlines and railways.
The research for AI for fault detection has been started by:
• creating and selecting datasets of the common defects in railways and bridges;
• choosing a platform to host the 3D models and the inspection pictures (with labels) of the desired infrastructure for inspection;
• developing machine learning (ML) algorithms for autonomous fault detection in the gathered pictures. In particular, the ML activity was mainly focused on bridges for which both supervised and unsupervised ML techniques have been investigated and exploited.
The research in the drone swarm started by defining the swarm functionalities, developing and testing parts in a simulated environment, and specifying the communication infrastructure between the drones as well as between drones and the cloud services.
The research in mission control and navigation started by defining the cloud infrastructure for monitoring and controlling the drones. The first prototype of the cloud services (monitoring, control, and automatic route calculations) has been designed, developed, and tested.
The developed drone prototypes are continuously being tested at the novel powerline setup at SDU, Odense. The powerline setup provides a controlled testing environment for the project results.
The Dissemination and Exploitation activities already started including publications, presentations in conferences, the organization of workshops including joint workshops with other H2020 projects in MG-02-08-2019 call, presentations to industries, and educational institutes. Master theses with project results have been also presented.
The Industrial Advisory Board has been established and is consisting of 11 experts from 11 companies and research institutes. The experts are end-users, AI, energy harvesting, drone design, and technology developers.
