Awarded contract
Published
Project Asurvey Phase 2
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Description
An automated aircraft inspection capability, for the RAF's Poseidon MRA-Mk1 (P8-A), enabling fast, accurate and detailed damage mapping of external airframe damage. Military aircraft are subject to numerous hazards due to harsh operating conditions, in-flight refuelling or loading and unloading during ground operations. Whether at their home base or during operational deployments, fleet availability and optimal aircraft condition are key to guarantee efficiency and safety of operations. As a proof of concept, Project ASURVEY will use autonomous drone technology at RAF Lossiemouth on Poseidon MRA-Mk1. As the air system is new into service, the CAMO will be able to establish a detailed baseline of the aircraft external condition and maintain a comprehensive history of damage to individual tail numbers. This will be able to feed into the aircraft structural integrity, and environmental protection working groups. The data produced for each tail number would further enable the CAMO's data exploitation working group, identifying common and unusual trends. Lot 1: An automated aircraft inspection capability, for the RAF's Poseidon MRA-Mk1 (P8-A), enabling fast, accurate and detailed damage mapping of external airframe damage. Military aircraft are subject to numerous hazards due to harsh operating conditions, in-flight refuelling or loading and unloading during ground operations. Whether at their home base or during operational deployments, fleet availability and optimal aircraft condition are key to guarantee efficiency and safety of operations. As a proof of concept, Project ASURVEY will use autonomous drone technology at RAF Lossiemouth on Poseidon MRA-Mk1. As the air system is new into service, the CAMO will be able to establish a detailed baseline of the aircraft external condition and maintain a comprehensive history of damage to individual tail numbers. This will be able to feed into the aircraft structural integrity, and environmental protection working groups. The data produced for each tail number would further enable the CAMO's data exploitation working group, identifying common and unusual trends.
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