Abstract
(Englisch)
|
The >50k large vessels across the world must be regularly monitored for corrosion and defects by human surveyors,
including dangerous and dirty confined GNSS-denied areas such as ballast water tanks and cargo holds. One person is
killed every week from accidents in these enclosed spaces, which despite having large surface areas, consist of many
smaller, confined compartments with narrow passages (40cmx60cm). However, a radical new approach is possible using
unmanned aerial systems (UAS or drones), by combining the latest developments in (1) collision-tolerant UAS, (2) multimodal
SLAM, (3) path planning, (4) autonomous drone racing, (5) aerial manipulation, (6) miniaturized NDT sensors,
and (7) ML-based defect identification. Only through a complete integration of these technologies is it possible to address
the challenges of deploying aerial robots in these challenging conditions. Equipped with automated AI-based scanning,
mapping, navigation and contact-based NDT, this has the potential to completely remove the need for human inspection.
Using a digital twin approach brings “superhuman” results: comprehensive semantic-aware detailed 3D mapping (1 cm
resolution) of large structures (>300 m), high resolution visual and NDT analysis (100um) and improved traceability
with automatically generated trend analysis. The ML for system mapping and NDT is trained with sociotechnical inputs
from experienced human inspectors.
Currently, a typical inspection costs >1M€ and requires 15 days (8 days inspection and 7 days travel to low cost Far
Eastern docks). A UAS-based inspection will take 1 day, with 1-2 days travel to an EU port at a cost of 200k€, saving
the industry >9B€ p.a. with 2.4MT of CO2 reduction. This consortium includes many of the world leaders in the field of
UAS-based inspection teamed with vessel owners and inspectors, enabling an end-to-end survey solution which would
save 50 lives/yr, and provide safer, more reliable, and accurate inspection data.
|
