Is the opportunity to establish the scientific, technical, commercial merit and feasibility of your proposed innovation.
The current methods for assessing military bridges rely on Preventative Maintenance Check and Services (PMCS) combined with fatigue monitoring crack gauges, which have proven insufficient for accurately determining a bridge’s remaining service life.
Bridge Health Monitoring System Read More »
The Ammonium Perchlorate Rocket Motor Destruction (ARMD) is designed for the closed disposal thermal treatment of Ammonium Perchlorate (AP) based rocket motors.
Innovative Operations for Treatment and Processing of Wastewater Read More »
Develop an emitter system-agnostic solution for threat representative waveform generation and validation.
Adaptive Filtering Techniques for Low-Cost RF Emitters Read More »
Development of cognitive decision aiding logic, utilizing machine learning and artificial intelligence constructs, to assist aviators in safely performing tactical flight very close to terrain.
Cognitive Terrain Flight Assistance Read More »
This topic seeks to develop autonomous drone swarm capability for watercraft operated in a riverine environment. The fielding of autonomous powered floating bridges will enable the Army to conduct unpredictable dispersed river crossings, increase crew survivability by removing the man from the craft, and reduce logistics footprint over the Improved Ribbon Bridge in use today by combining both payload capacity and powertrain into a single craft. The development of an autonomy package for multiple dispersed floating bays to interact separately and jointly is the key technology to bring this capability to the 2040 battlespace.
Autonomous Robotic Bridging Read More »
The objective of this topic is to apply Large Language Models (LLMs) and/or other Artificial Intelligence (AI) approaches to support and automate warfighter’s system’s integrations. This will pertain to problems with data unification and interoperability regardless of the target system, source system, or data format. It will focus on usage in tactical environments to assist and provide reliable performance, regardless of echelon level.
Artificial Intelligence for Interoperability Read More »
Current ground-based radar systems cannot meet the detection needs of evolving longer range threat systems without sacrificing scan times. The Army needs a solution, such as novel signal processing techniques, that can be implemented on existing radars that will provide improvements in probability of detection at longer ranges. Solutions must not impact current scan time requirements.
Radar Signal Processing Improvements for Probability of Detection Read More »
Automated Course of Action (CoA) recommendation at the Unit of Action. Currently, it takes units at the Battalion (BN) echelon several hours to use the Military Decision-Making Process (MDMP) to generate and vet CoA options.
Leveraging state-of-the-art Artificial Intelligence/Machine Learning (AI/ML) algorithms will speed up this process by an order of magnitude, allowing systematic replanning during the execution phase of operations. This will improve mission success and reduce risk to force in combat operations. It will also enable the mobile, distributed command post concept.
Automated Course of Action Generation Read More »
Develop and implement a secure wireless data transfer solution for Predictive Logistics. This solution must enable the seamless movement of collected logistics data from military platforms to a central location where Unit Commanders and Maintainers can visualize and analyze this data.
Secure Wireless Data Transfer Solutions for Predictive Logistics Read More »
The proposed topic will develop a Large Language Model (LLM) tailored to reduce the risk of traditional and emerging Artificial Intelligence (AI) and Machine Learning (ML) adversarial attacks on aviation and missile systems.
Large Language Models for System Security Engineering Analysis Read More »
