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.

The IoT market is young but has a huge need for application-specific sensors to gather data, process it and provide valuable decision-making data. Since 2012 Terabee has created and commercialised optical Time-of-Flight distance sensors, with world-leading performance for the given size, weight and sensor price. The technology is deployed like ‘bricks’ where one or multiple sensors are used in a simple plug and play way. Leveraging its latest generation sensors, Terabee is gearing up for IoT applications through “Application Products” that will meet the technical needs of specific markets. In addition, Terabee has created a unique business approach it calls “lean sensing”, where less data is gathered but in more reliable and redundant ways in order to reduce compute, data transfer and control system complexity. From 2 years of feasibility study based on field tests, Terabee has selected 6 mature Application Products to industrialise during the Phase 2 project. These products may include one or more single-pixel or multi-pixel sensors, processing and algorithms, power supply and communication protocols and, if needed, dust and water-resistant casings to withstand harsh environments. Demand for our type of sensors is estimated at 5 billion units in 2020, growing 25-35% p.a. The Total Addressable Market is estimated at 8 billion sensors in 2025. This project is the cornerstone of a strategy to shift from being Technology-led to Market-led, capitalising on a growing demand for ready-to-use Application Products in the IoT and Mobile Robotics markets. During the project, Terabee will finalize 6 Application Products while running pilots with 4 Industrial companies with which field tests have already taken place. In parallel, the Go-to-Market plan will be created through detailed Marketing, Communication and Business Development actions.

The MOMIT project will develop innovative products and solutions supporting the maintenance process of railway infrastructures. MOMIT concept is based on the exploitation of unmanned technologies as Earth Observation satellites and RPAS-borne sensors. Starting from collected data analysis, MOMIT will bring at cutting edge level the remote sensing technology: developing advanced post processing chains, data fusion, automation, defining new indicators from estimated parameters, MOMIT will design new operational workflows able to support intelligent asset management. MOMIT will adopt a multi scale approach: Satellite and RPAS data will be combined in order to maximize their benefits and characteristics. A first overall analysis (with satellite and over long sections) will guide the detailed analysis and trigger specific preventive actions. Thus, maintenance activities are guided by this combined analysis with a general optimization of resources. Effectiveness and efficiency of proposed solutions will be demonstrated by six main application cases, validated in a real operational environment: - Ground movements: interferometry derived by SAR satellite data analysis will adopt to define tools and indicators supporting the user for detailed analysis and preventive actions planning - Hydraulic activities: a combination of optical and radar satellite data will be used to monitor soil moisture and water bodies close to the track - Natural hazards: anomalies along the track related to natural phenomena (as vegetation growth) will be monitored by the use of satellite data. - Electrical system: RPASs will be equipped with innovative sensors to monitor electrical effects impacting on the infrastructure efficiency - Civil engineering structures: a combination of satellite and RPAS data will be used to identify possible criticalities to the infrastructure - Safety: anomalies and illicit activities along the track will be monitor by the use of optical a radar satellite data