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DroneOps Ltd offers Research & Development of Small Unmanned Aerial Systems (SUAS) and robotic technologies through innovation and system integration together with construction of the drones, training for their use and ongoing technical support.

DroneOps Ltd participated in the Army Warfighting Experiment 2018 (AWE2018) to research and develop a prototype UAV to carry out a number of tasks required by the MoD in relation to identifying anomalies under the ground with some specific military parameters. It is the intention of DroneOps Ltd to continue the research using grants won from opportunities such as the GX Project (see next item) and other ongoing Government initiatives that DroneOps Ltd is expediting.

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June 2019

DroneOps Ltd is pleased to announce the signing of a Partnership Agreement with NewcastleGateshead Initiative ( ) and the University of Northumbria in Newcastle ( The GX Project – the legacy project of the Great Exhibition of the North- is part-funded by the European Regional Development Fund ( and delivered by NewcastleGateshead Initiative (NGI) (, in partnership with the Innovation SuperNetwork and Newcastle City Council.

This ‘GX Collaborate Partnership’ will enable Drone Ops Ltd – following its participation in the Army Warfighting Experiment 2018 (AWE18) - to deliver a project over the next 5 months, working with Northumbria University to undertake research and development linked to the long standing ambition of DroneOps Ltd to develop an Unmanned Aerial Vehicle (UAV) as a flying platform for Ground Penetrating Radar (GPR) enabling landmines and other underground anomalies to be easily and safely located and identified.

At present, military and civilian personnel are put at risk when using GPR for the clearance of explosive devices. A GPR expert is also required to interpret the GPR data. This project comprises a number of complex work packages: one of which, involves the research, by Northumbria University, of the simulations of the GPR antenna, which is an initial but integral step in being able to train a neural network to interpret the data acquired from the sensor.


The Core
Science Central
Newcastle upon Tyne
United Kingdom

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