The United States Space Force (USSF) is seeking innovative solutions through the Small Business Innovation Research (SBIR) program for Project SpaceKnight, an interactive AI simulation aimed at enhancing training for space sustainment and logistics in contested environments. The primary objective is to develop a proof-of-concept AI-driven strategy game that simulates logistics planning, incorporating realistic constraints such as orbital mechanics and adversarial disruptions, to prepare Guardians and logistics planners for complex space missions. This opportunity is critical for advancing training methodologies in space logistics, with a focus on creating a minimal viable simulation environment during Phase I, followed by a fully operational platform in Phase II. Interested parties should note that the solicitation is set to open on July 23, 2025, with applications due by August 20, 2025, and can find more information at the official SBIR website.

## Description

The USSF requires advanced training tools to prepare Guardians and logistics planners for the complex challenges of space sustainment, including adversarial interference, orbital constraints, and dynamic resupply conditions. Traditional wargaming and training platforms lack the interactivity, realism, and adaptability needed to prepare personnel for next-generation space logistics missions. Project SpaceKnight will address this gap by developing a proof-of-concept, AI-driven strategy game that simulates logistics planning and sustainment in contested space environments. This Phase I effort will focus on:- Designing core game mechanics for both single-player and multiplayer scenarios;- Modeling realistic constraints such as launch timing, fuel, orbital mechanics, and adversarial disruption;- Prototyping AI-driven scenario generation to reflect real-world mission variables;- Exploring immersive learning options using augmented reality/virtual reality (AR/VR) and advanced human-machine interfaces;- Demonstrating how the simulation environment can support decision-making, CONOPS exploration, and supply chain risk analysis.The objective is to establish feasibility, validate early design elements, and lay the groundwork for a full-featured training and wargaming platform in future phases.

## Objective

The goal of this effort is to design and demonstrate the feasibility of an Artificial Intelligence (AI)-enabled, interactive strategy game prototype to support training and simulation for Space Logistics and Sustainment. This Phase I effort will focus on conceptualizing game mechanics, modeling realistic logistics scenarios, and developing a minimal viable simulation environment that integrates decision-support elements, human-machine interaction, and adversarial modeling. The prototype should provide a foundation for immersive training and concept of operations (CONOPS) experimentation aligned with U.S. Space Force (USSF) sustainment strategy.

## Phase I

The Phase I objective is to establish the feasibility of SpaceKnight as an AI-enabled, game-based training and simulation tool for space logistics and sustainment. This phase will focus on conceptual design, initial prototyping, and early validation of the system's training value and operational relevance. Key activities include:- Develop the conceptual architecture and game design, including AI logic, user interaction models, and scenario components.- Create a functional prototype capable of simulating at least one realistic logistics or sustainment scenario, incorporating basic adversary dynamics, launch constraints, or resource limitations.- Build an AI-driven scenario generation framework that enables dynamic mission variables and training variability.- Conduct stakeholder interviews with USSF logistics personnel, Space Systems Command (SSC) training teams, and other relevant users to inform use cases and requirements.- Evaluate and document how the prototype enhances decision-making, CONOPS exploration, and learning outcomes.Deliverables may include:- Conceptual game design and system architecture document.- Prototype demonstration of a simulated logistics/sustainment scenario.- Initial AI-based scenario generation engine.- Use case study on training and decision impact.- Stakeholder interview report and requirements validation summary.

## Phase II

The Phase II objective is to advance SpaceKnight from a Phase I prototype to a fully operational training and simulation platform for space logistics and sustainment. This phase will deliver a complete, AI-enabled game environment capable of supporting multi-user training, immersive planning, and digital decision support aligned with real-world mission variables. Key activities include:- Develop and deploy a complete version of the SpaceKnight platform, incorporating realistic logistical and operational constraints such as fuel consumption, orbital mechanics, launch windows, and adversary behavior.- Expand system functionality to support both turn-based and real-time scenarios in single-player and multiplayer formats, enabling distributed team exercises.- Integrate AR/VR capabilities for enhanced immersion and scenario visualization, with support for advanced human-machine interfaces (e.g., voice, gesture, touchscreen).- Build a robust analytics dashboard to track user performance, mission outcomes, and training metrics.- Conduct testing in tabletop exercises (TTX) and wargaming environments to validate training efficacy and operational planning utility.- Initiate integration with existing DoD training and learning platforms, ensuring alignment with USSF and Joint logistics frameworks.Deliverables may include:- Fully operational SpaceKnight simulation platform (unclassified, with capability for classified scenario extensions).- Multi-user functionality for collaborative, distributed exercises.- Constraint engines simulating mission realism (e.g., launch infrastructure, ground station coverage, resource availability).- Immersive AR/VR module and interactive planning interfaces.- Mission analytics dashboard and performance tracking tools.- Testing and training report summarizing system effectiveness in operational exercises.- Transition and deployment plan for DoD adoption and broader training integration.

## Phase III: Dual Use Applications

For Phase III military applications, SpaceKnight will transition into an operational training, planning, and wargaming platform for use across SSC, USSF, and broader Joint logistics communities. Key applications include:- Training Tool for Logistics Forces: Enhances Guardian and Airman readiness through immersive, scenario-based learning focused on contested, orbital sustainment operations.- Strategic and Tactical Wargaming: Supports CONOPS development and mission rehearsal through dynamic adversary modeling and real-time decision environments.Integration with Digital Twin Systems: Enables synchronization with broader planning ecosystems (e.g., VS-CDF or the Spaceport of the Future Common Operating Picture (COP) Logistics Module) for end-to-end simulation and decision support.For commercial applications, the underlying AI-driven simulation engine and gamified interface can be adapted for commercial use in sectors including space logistics, supply chain training, and strategic planning. Use cases include:- Aerospace &amp; Logistics Workforce Development: Provides high-fidelity, simulation-based training for companies managing spaceport operations, satellite logistics, or intermodal transportation.- Space Sector Investment &amp; Concept Testing: Serves as a strategic learning environment for commercial space startups, incubators, and venture stakeholders to test logistics models and resiliency planning.- Academic &amp; Defense Industry Simulation Tools: Offers customizable wargaming environments for defense contractors, think tanks, and universities conducting research on space sustainment and supply chain dynamics.For the transition plan, SpaceKnight will be transitioned via coordination with SSC, training directorates, and defense education institutions for military use. In parallel, commercial licensing opportunities will be explored with aerospace firms, logistics tech developers, and academic partners seeking simulation-based decision support platforms. The anticipated Technology Readiness Level (TRL) at Phase III Entry is TRL 8 or 9, following successful validation in training environments and operational planning exercises.

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