Black River researches and develops advanced resource management and resource allocation techniques such as managing swarms of UAVs, evading air defense systems, and managing space sensor tasking.

Our route planning algorithms employ both constrained linear optimization and Multi-Agent Reinforcement Learning (MARL) approaches. For sensor management, we’ve applied multiple solution methods that range from guided search genetic algorithms to approximate dynamic programming for managing complex multisensor tasking schedules. Underlying the work in this area for sensor tasks and route path scoring is a common currency based upon the use of information-theoretic scoring.

These efforts have been tested and evaluated in both laboratory environments and live-fire exercises. All of them support a range of missions such as multisensor area surveillance, high-value threat monitoring, and missile intercept prioritization.