Leonardo announced today the crew of AW159 Wildcat helicopter controlled an unmanned aerial vehicle (UAV) from the cockpit.
The helicopter-UAV teaming took place on September 12 in the UK. The demonstration was part of the British Army’s Manned-Unmanned Teaming (MUMT) themed Army Warfighting Experiment (AWE) 19, and was planned and executed by Dstl and took place on Salisbury Plain in September.
These trials build on simulation based development conducted under the Dstl funded AMS DE-RISC programme. This successful demonstration is now expected to inform the MUMT capability roadmap for both the UK MoD and Leonardo.
The semi-autonomous UAV is built by Callen-Lenz Associates.
In this instance, MUMT is when a helicopter crew controls a UAV from the helicopter like it was an onboard sensor being controlled from the cockpit. By integrating control of the UAV into the Wildcat Mission System, Leonardo was able to minimise the pilots’ workload allowing them to focus more on the mission whilst simultaneously controlling the UAV - this is the first time such an integrated capability has been demonstrated in the UK on a military aircraft. A ‘Gateway Processor’ supplied by Callen-Lenz Associates was used to interface with its semi-autonomous UAV.
The Leonardo solution allows the Wildcat crew to control both the flight path and payload of the UAV (a capability known as Level of Interoperability (LOI) 4) using an efficient and effective task based Human Machine Interface (HMI), rather than the more operator intensive approaches employed on other systems.
Combining the strengths of manned and unmanned platforms, MUMT has the potential to play a transformative role by increasing the situational awareness, tempo, lethality, survivability and combat mass of aviation forces, significantly reducing crew workload allowing pilots to focus on the mission at hand.
Teaming of manned aircraft with unmanned air systems (MUMT) enhances air support capability in both the Land and Maritime environments. It also enables extended and complex operations to be conducted with a mix of platforms and systems.