Indian Armed Forces are undergoing for induction of large number of unmanned aerial vehicles (UAVs). The Indian Army for instance has floated a series of Request for Information in Decembcer last year for UAVs for varied functions ranging from surveillance, logistics to attack.
The armed forces have been increasingly demonstrating the employment of UAVs at Defence Expos and other ceremonial events indicating swarm drone caapbilities.
While induction of UAVs is keeping in line with recent trends in warfare as their effectiveness has been demonstrated in the recent war in Ukraine, for effective utilisation of unmanned assets manned teaming would be essential. The concept and employment is being described herein
Concept of Manned-Unmanned Teaming (MUM-T)
The US Army Aviation Centre (USA ACE) defines MUM-T as synchronised employment of soldiers, manned and unmanned air and ground vehicles, robotics, and sensors to achieve enhanced situational understanding, greater lethality, and improved survivability.
The BAE Systems underlines that, “Manned-Unmanned Teaming (MUM-T) is revolutionising mission autonomy, through greater situational awareness and decision-making capabilities.” The combined employment of unmanned and manned military assets provides the unique capabilities of each system to be leveraged for the same mission. According to the BAE Systems, ‘The US defence sector is highly involved in the development and deployment of MUM-T for its potential to increase capacity and responsiveness, broaden capabilities, and reduce risk to military personnel as it supports mission success”.
Adaptation of MUM T and Development
Technology progression has led to employment of unmanned aircraft systems (UAS) in particular for military operations. There is a perpetual race between the user – the military and the technology developer as demands from unmanned systems are continuously increasing.
A research paper published in 2015, Army Aviation Manned-Unmanned Teaming (MUM-T): Past, Present, And Future gives detailed progress of the technology and testing by the US armed forces along with the future trajectory to achieve targeted technological achievement with respect to the MUM-T.
Given the varied success in integrating artificial intelligence (AI) and machine learning capabilities over the last two decades, Tistan Sauer, land domain analyst at GlobalData observes that this has enhanced the ‘viability and effectiveness of all joint formations in future operations.’ To understand the study and research work better, the US department of defence lists five levels of interoperability (LoI) which determines the amount of control and coordination a ‘manned’ operator exerts over unmanned platforms. These are:
LoI 1: Verbally communicate with the UAS operator via radio
LoI 2: View UAS sensor imagery in real-time
LoI 3: Control UAS sensor payload orientation
LoI 4: Control UAS aircraft position via waypoint navigation
LoI 5: Assume complete control of UAS, including take-off and landing
As Tristan Sauer observes, ‘The current limitations of the MUM-T concept revolve around the LOI scale, as higher levels of control are typically associated with several detrimental factors, including sensory overload, task saturation and reduced situational awareness. However, Elbit Systems has demonstrated that advances in AI technology will allow for enhanced autonomy and redundancy amongst future military unmanned platforms, thus drastically reducing both the logical and cognitive burdens of MUM-T in future operations.’ As per the Research Paper, “The first major follow-on to the preliminary MUM studies was the Airborne Manned/Unmanned System Technology Demonstration (AMUST‐D) in 2002”.
This program sought to develop and demonstrate new technologies built specifically for interoperability with UAS from manned helicopters. The program consisted of two related efforts: the Warfighter’s Associate, led by Boeing, which provided control of UAS from the co-pilot gunner (CPG) station of the Apache; and Mobile Commander Associate, led by Lockheed Martin, which provided UAS control from the Army Airborne Command and Control System (A2C2S) in the back of the Blackhawk.
Both systems sought to transition CDAS functionality originally developed for the Rotorcraft Pilot’s Associate, which included advanced autonomous behaviours, data fusion techniques, and intelligent flight routing – all capabilities intended to free up operator cognitive resources, allowing them to focus their limited attention on the battle rather than aircraft management. The Research Paper states that AMUST-D program also sought to overcome the interface shortcomings identified by the previous MUM studies. Although the Mobile Commander Associate system was never formally fielded, due to the A2C2S system never being integrated into the Blackhawk fielding plan, the Warfighter’s Associate system continued development until eventually being an integral component in the Apache AH-64D Block III upgrade, as well as the AH-64E model.”
Present Status US
The present status is as impressive as the initial trials of the tech integration. As per the research paper, ‘The AH-64E is the first fielded aircraft to provide manned platform crew members with LOI 3 and 4 capability, allowing them to not only view live imagery collected from the UAS sensor but also take direct control of the sensor and even the UAS aircraft itself if desired.’
Moreover, ‘one of the primary goals of the Warfighter’s Associate system, originally developed under the AMUST-D program, was to utilize existing controls and displays already onboard the aircraft for MUM-T operations as per the Research Paper.
The CPG’s TEDAC (Target Acquisition and Designation Sights (TADS) Electronic Display and Control) system provides standard controls for UAS teleoperation, such as manipulating the pan/tilt/zoom of the sensor payload, alternating between a variety of UAS sensors, and activating the laser designator.
In addition to these standard control methods, the system also provides two unique control methods that are significant workload reducers for MUM-T operations. The first unique mode is the sensor guide mode, which is sometimes informally referred to as LOI 3.5, because it provides the operator with complete control over the sensor (LOI 3) with partial authority over the vehicle’s flight path. This method of control allows the operator to only focus his attention on the task that is important to him, viewing a particular region of the ground, without the additional workload associated with managing the aircraft itself. Another method used to reduce the workload is the sensor slave functionality.
This function allows the operator to instantly orient the UAS sensor to image the same geographic position on the ground that is currently viewed by the Apache’s own sensor (or vice versa, slaving the Apache sensor to the UAS sensor position). This technique simplifies the common task of coordinating target locations between the manned and unmanned systems, allowing all team members to more quickly and accurately establish a common operator picture.’
In the recent developments as pointed out by Tristan Sauer, “Elbit Systems illustrated how robotic autonomous systems (RAS) technology would enable UAS and UGV swarms to conduct a range of different tasks, including navigation, reconnaissance, resupply and forward deployment of assets, with minimal oversight from human controllers. Using AI-enhanced navigation and target recognition software, both the THOR mini-UAS and PROBOT UGV can deploy, operate and return to base autonomously, thus reducing the workload of ‘manned’ elements and allowing them to shift their focus to other tasks.
Elbit’s team also demonstrated how AI-enhanced UAS formations were capable of semi-autonomously deploying additional platforms or sensors in the field and consequently ‘growing’ their swarm organically.”
Technologies Required
‘Although the specific technological improvements expected to have the greatest impact have yet to be established by the TRAC MUM-T 2030 study, the science and technology (S&T) community has already initiated efforts toward developing improved MUM-T capabilities. One such effort currently in progress is the SCORCH (Supervisory Controller for Optimal Role Allocation for Cueing of Human Operators) program, a collaborative effort between researchers from the AMRDEC Aeroflightdynamics Directorate (AFDD), United Technologies Research Center (UTRC), and the University of California, Santa Barbara (POC: Amit Surana, SuranaA@utrc.utc.com).
The SCORCH program will develop and evaluate cognitive decision-aiding tools and sensor tasking automation that will enable aviators to effectively command teams of up to three advanced UAS simultaneously up to LOI 4 in support of a variety of missions and roles. The research is focused on three areas identified through prior research efforts as critical for a single operator to manage multiple UAS in support of a common mission: the pilot-vehicle interface, a sensor management aide, and attention allocation aide.’
‘The pilot-vehicle interface developed for the SCORCH program is representative of cockpit designs expected to be fielded in near-future Army helicopters. The sensor management aide aims to offload the operator workload for lower-level sensor control tasks, freeing mental resources to focus on higher-level information processing and decision-making. The final SCORCH system component is the attention allocation aide, an adaptive CDAS with the goal of improving the operator’s visual search behaviour.’
The Way Ahead
With ongoing developments, the future aspects of the MUM-T depend heavily on confirming technological achievements combined with pertaining and evolving warfare strategies. The current operability is inclined towards the human control over the machine or AI system where future endeavours must aim to remove ‘the need for a human to operate an unmanned platform’s navigation and target identification systems, the operator can then focus on more complex tasks such as relaying intelligence or coordinating manoeuvres with the other elements of a manned-unmanned unit formation.
Application of the MUM-T concept to military UGVs is expected to be the way ahead as current UGV platforms still require a significant level of human input when navigating complex terrain is pointed out by Tristan Sauer.
In addition as military organisations and defence contractors worldwide continue to invest in autonomous drone swarm technology, the ratio of manned to unmanned systems per MUM-T formation will likely decrease over time, as unmanned platforms become increasingly independent and reliable which is inevitable.
[Research Extracts and Compilation by Harshita Singh Panwar]