• TOTAL CASH PRIZES OFFERED: $250,000
• TYPE OF CHALLENGE: Ideas, Technology demonstration and hardware, Scientific
• PARTNER AGENCIES | FEDERAL: Office of Naval Research Science and Technology (ONR), NavalX Midwest Tech Bridge
• SUBMISSION START: 12/10/2020 02:00 PM ET
• SUBMISSION END: 01/29/2021 02:00 PM ET
Description: Artificial Intelligence for Small Unit Maneuver (AISUM) combines Naval Expeditionary Warfare and Special Operations Forces (SOF) tactical maneuver elements with Robotic Autonomous Systems (RAS) to create a low risk human machine maneuver element that gains, maintains and extends access in complex, contested and congested areas, providing a decisive advantage and precision application of effects.
Over the past 20 years the SOF community perfected the combination of its tactical maneuver elements and small arms precision fire with overhead unmanned and remotely piloted airborne Intelligence, Surveillance, and Reconnaissance (ISR) in its aerial delivered strike to precisely find, fix and finish networked threats. However, these non-state actors mostly operated in a two-dimensional battlespace that was mainly rural and urban sprawl, with little to no access to Electronic Warfare (EW) tools.
Though the Special Operations community have become masters of the 2-dimensional threat environment over the past two decades, with today’s emerging threat environments, adversaries attempt to contest all domains with advanced technologies and take advantage of the complex and congested 3-dimensional battlespace. This reduces the effectiveness of SOF tactical maneuver elements, ISR and precision fires, creating the inability to maintain continuous airborne ISR feeds and key communications and navigation bands in the electromagnetic spectrum in these dense urban clutter environments, leaving our tactical maneuver elements challenged.
For example, in a mission to infiltrate and obtain information or an asset from a sub terrain tunnel system in a contested and congested threat environment, AISUM could be used to gain intelligence and minimize human risk. Conceptually, satellite imagery would provide the initial data used to generate a 3-dimensional terrain map of an area of operations, allowing mission planners, operators and drones to plan, train and rehearse within the simulated environment. These activities allow the team to develop and optimize specific tactics, techniques and procedures.
This Prize Challenge reaches out to the defense, academic and industrial community to enhance research and development in the field of artificial intelligence for small unit maneuver. The objective of the Prize Challenge is for the development of an algorithm to enhance the maneuver and reconnaissance capabilities of autonomous drones within defined scenarios. The objective includes the utilization of the Government Furnished Property (GFP) drones, sensors, and onboard processing.
For complete challenge information, click here.