CLOSTRA INC — Department of Defense SBIR Phase II: A214-045
CLOSTRA INC — SBIR Phase II award from Department of Defense.
Phase II SBIR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- At $1,699,990, this is a large obligation for typical SBIR Phase sizing — worth reviewing for scope breadth and teaming opportunity.
- Topic code A214-045 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $1,699,990
- Agency
- Department of Defense · Army
- Program / Phase
- SBIR · Phase II
- Topic
- A214-045
- Solicitation
- 21.4
- NAICS
- —
- Place of performance
- FL
- Period
- 2023-07-20 → 2025-02-28
Description
Robust collaboration is needed between different agents in various Unmanned Aerial/Ground Systems (UxS). ML/AI development has enabled development of a graph neural network (GNN)-based swarm control algorithm. Clostra’s GNN-Swarm uses a GNN framework for mapping relationships between all members of a UxS swarm, and deep reinforcement learning (DRL) for organizing, training, optimizing, and robustifying swarm behavior towards a specific goal. GNN’s allow swarming agents to be gracefully added or dropped from the current swarm graph as GNNs function well with incomplete information. Critically, use of GNN-based graphs allow agents to quantitatively determine the informational validity (or likelihood of noise) of received data in contested RF or communication-poor environments. Current GNN control solutions are based on Laplacian matrices, which are hard coded and not responsive to real-time changes to the agent or graph (for example, a team member is added or lost). A more flexible, robust approach is needed, which easily takes into account adding/dropping agents from a swarm (and complex goals) without significant customization or lengthy, expensive training: Clostra’s GNN-Swarm. By the end of Phase II Clostra will have our GNN-Swarm algorithm installed and testing in a swarm of UAVs in various outdoor and/or indoor environments.