Summary
THE PROBLEM
The inspection of underground infrastructure is done by operators using expensive machinery, with associated high costs (within the range 15 - 60 k€/km), high risks and safety issues. Unmanned Aerial Vehicles can replace inspection teams in these demanding tasks, reducing the cost by 90%, but no product in the market is able to operate autonomously in GNSS-denied environments and to produce reliable 3D mapping of the sites, sending high quality information to the system/person in charge of taking decisions.
AUTOFLYMAP SOLUTION
HS has developed the first drone able to fly autonomously in underground environments (GNSS-denied) and capable to produce high quality 3D textured models for mapping and inspection of indoor scenarios. The solution is applicable in several sectors requiring eventual or regular inspection of underground sites without the need of operator’s presence at visual distance: e.g. tunnel construction, underground infrastructure inspection and maintenance, rail and road operation, facilities management, mining, etc. This breakthrough solution is achievable thanks to the development of two proprietary technological solutions: 1) indoor multi-sensor-based positioning system; 2) high-performance on-board data gathering sensors sets and raw data processing solution for 3D mapping.
THE FEASIBILITY STUDY
HS will develop a detailed technical and business feasibility analysis, to assess the details of the service to be provided (procedures, data encryption, user interfaces, sensors update and functionalities of the flying robot), to quantify the achievable markets and to refine the Business Model to be implemented in the Market Entry phase. The targets are: i) Cost of Production (Robot Bill-Of-Materials) < 6 k€; ii) Service model confirmed at > 6 k€/km; iii) Letters of Intent signed with one international distributor; iv) 2 end users selected for the demo tests planned for Phase 2.
The inspection of underground infrastructure is done by operators using expensive machinery, with associated high costs (within the range 15 - 60 k€/km), high risks and safety issues. Unmanned Aerial Vehicles can replace inspection teams in these demanding tasks, reducing the cost by 90%, but no product in the market is able to operate autonomously in GNSS-denied environments and to produce reliable 3D mapping of the sites, sending high quality information to the system/person in charge of taking decisions.
AUTOFLYMAP SOLUTION
HS has developed the first drone able to fly autonomously in underground environments (GNSS-denied) and capable to produce high quality 3D textured models for mapping and inspection of indoor scenarios. The solution is applicable in several sectors requiring eventual or regular inspection of underground sites without the need of operator’s presence at visual distance: e.g. tunnel construction, underground infrastructure inspection and maintenance, rail and road operation, facilities management, mining, etc. This breakthrough solution is achievable thanks to the development of two proprietary technological solutions: 1) indoor multi-sensor-based positioning system; 2) high-performance on-board data gathering sensors sets and raw data processing solution for 3D mapping.
THE FEASIBILITY STUDY
HS will develop a detailed technical and business feasibility analysis, to assess the details of the service to be provided (procedures, data encryption, user interfaces, sensors update and functionalities of the flying robot), to quantify the achievable markets and to refine the Business Model to be implemented in the Market Entry phase. The targets are: i) Cost of Production (Robot Bill-Of-Materials) < 6 k€; ii) Service model confirmed at > 6 k€/km; iii) Letters of Intent signed with one international distributor; iv) 2 end users selected for the demo tests planned for Phase 2.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/832329 |
| Start date: | 01-01-2019 |
| End date: | 30-06-2019 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
THE PROBLEMThe inspection of underground infrastructure is done by operators using expensive machinery, with associated high costs (within the range 15 - 60 k€/km), high risks and safety issues. Unmanned Aerial Vehicles can replace inspection teams in these demanding tasks, reducing the cost by 90%, but no product in the market is able to operate autonomously in GNSS-denied environments and to produce reliable 3D mapping of the sites, sending high quality information to the system/person in charge of taking decisions.
AUTOFLYMAP SOLUTION
HS has developed the first drone able to fly autonomously in underground environments (GNSS-denied) and capable to produce high quality 3D textured models for mapping and inspection of indoor scenarios. The solution is applicable in several sectors requiring eventual or regular inspection of underground sites without the need of operator’s presence at visual distance: e.g. tunnel construction, underground infrastructure inspection and maintenance, rail and road operation, facilities management, mining, etc. This breakthrough solution is achievable thanks to the development of two proprietary technological solutions: 1) indoor multi-sensor-based positioning system; 2) high-performance on-board data gathering sensors sets and raw data processing solution for 3D mapping.
THE FEASIBILITY STUDY
HS will develop a detailed technical and business feasibility analysis, to assess the details of the service to be provided (procedures, data encryption, user interfaces, sensors update and functionalities of the flying robot), to quantify the achievable markets and to refine the Business Model to be implemented in the Market Entry phase. The targets are: i) Cost of Production (Robot Bill-Of-Materials) < 6 k€; ii) Service model confirmed at > 6 k€/km; iii) Letters of Intent signed with one international distributor; iv) 2 end users selected for the demo tests planned for Phase 2.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
Images
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Geographical location(s)
Structured mapping
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