OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Sustainment & Logistics The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 3.5 of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: The goal for this effort is to develop an Autonomous Space Cargo Network (ASCN) that integrates Artificial Intelligence (AI)-driven automation, autonomous robotics, and digital twin technology to modernize and optimize cargo handling and logistics operations at the Space Joint Movement Complex (SJMC) and across the Department of Defense's (DoD) space mobility enterprise. The ASCN will improve operational efficiency, accuracy, and resilience by enabling real-time cargo visibility, autonomous load planning, and adaptive logistics execution. This capability will form the foundation for a scalable, cybersecure, and interoperable logistics framework supporting space sustainment missions in both contested and commercial environments. DESCRIPTION: The SJMC is envisioned as the central logistics hub for DoD space operations, supporting rapid deployment, sustainment, and agile mobility. Current cargo handling and logistics processes are heavily manual, lack real-time adaptability, and are not optimized for space-based supply chains or contested logistics environments. To address these gaps, the ASCN will deliver an integrated, AI-driven logistics automation platform designed to support the SJMC and broader DoD logistics operations. The ASCN will combine autonomous robotics, intelligent decision-support, and digital twin technology to enable full-spectrum cargo management from warehouse to orbital interface while increasing speed, precision, and resilience. Key capabilities include: 1. Autonomous Cargo Handling & Transport Optimization This includes robotic forklifts and cargo handlers for autonomous loading/unloading, AI-based routing, prioritization, and adaptive logistics workflows, and seamless integration with space, air, and ground mobility operations. 2. AI-Driven Logistics Command & Control This includes real-time AI controller for cargo flow, load planning, and schedule optimization, weight-based load verification and automated resupply workflows, integration with the Spaceport of the Future's Common Operating Picture (SPOF COP). 3. Machine Learning for Mission Adaptability This includes predictive analytics for storage allocation and resource positioning, dynamic mission reprioritization and automated contingency planning, and visibility and orchestration across all classes of supply. 4. Commercial & Military Logistics Interoperability This includes compatibility with U.S. Transportation Command (USTRANSCOM), Space Systems Command (SSC), Defense Logistics Agency (DLA), and commercial launch providers, joint DoD-commercial protocol development for space cargo integration, and enhanced operational readiness across government and industry supply chains. 5. Cybersecure & Resilient AI Robotics Architecture This includes blockchain-secured logistics tracking and tamper prevention, quantum-resistant AI algorithms for autonomy assurance, and Zero Trust cybersecurity framework for secure operations at all classification levels. This effort will lay the foundation for a future-ready, modular, and scalable space logistics infrastructure, aligned with U.S. Space Force (USSF) sustainment strategy and capable of supporting both terrestrial and extraterrestrial cargo networks. PHASE I: The Phase I objective is to develop a conceptual design and functional prototype for the ASCN a system that integrates AI-enabled robotics, cargo handling automation, and logistics optimization for space-focused environments. The effort will evaluate the feasibility of supporting standard DoD platforms, such as fully loaded 463L pallets, and determine the scalability of the solution for future autonomous cargo transport at the SJMC. Technical approach consideration include: - Simulate AI-enhanced cargo workflows within the SJMC, focusing on load planning, routing, and weight distribution using real-time sensing technologies. - Design and model robotic automation frameworks for autonomous cargo handling, scheduling, and dynamic load stabilization. - Assess integration with existing DoD logistics platforms and commercial space operations, including compatibility with USTRANSCOM, DLA, SSC, and commercial launch provider networks. - Conduct stakeholder engagements with logistics planners and operational units to refine system requirements. - Execute preliminary load balance and maneuverability testing using 463L pallets to identify mechanical design needs. - Perform energy efficiency and power requirement analyses to inform autonomous runtime and charging strategies. Phase I deliverables include: - Conceptual design document detailing system architecture, autonomy layers, and AI integration pathways. - Initial prototype demonstration showcasing AI-based cargo management logic, load balancing, and sensing capabilities. - Feasibility study covering integration potential with DoD systems, environmental resilience, scalability, and power/energy assessments. - Phase II roadmap outlining test campaigns, system modifications for larger payloads, and milestones for operational prototype development. PHASE II: The Phase II objective is to design, develop, and demonstrate a fully operational prototype of the ASCN capable of autonomous cargo handling, intelligent logistics coordination, and mission adaptability in contested or austere logistics environments. This phase will validate the system's ability to improve cargo throughput, reduce human intervention, and integrate with both DoD and commercial logistics systems. Technical focus areas include: - Build and integrate a full-scale ASCN prototype with autonomous robotic handlers, real-time cargo identification, and secure communications. - Implement advanced AI models for adaptive cargo prioritization, dynamic routing, and autonomous load planning. - Integrate with existing DoD logistics platforms such as USTRANSCOM, the Spaceport of the Future's COP Logistics Module, and commercial systems where applicable. - Conduct operational testing in representative logistics environments (e.g., Space Launch facilities, Distribution Hubs). - Collect performance data for load accuracy, handling speed, mission responsiveness, energy usage, and system reliability. - Demonstrate predictive maintenance and mission adaptability functions under simulated disruption scenarios. Phase II deliverables include: - Fully functional ASCN prototype, including AI, autonomy, and system integration components. - Operational test campaign report, capturing performance metrics, environmental tolerance, and logistics throughput improvements. - AI performance evaluation, including model training, learning adaptability, and logistics decision support outputs. - Integration documentation detailing system compatibility with SSC, DLA, USTRANSCOM, and commercial logistics platforms. - Phase III transition plan, outlining commercialization strategy, scaling pathways, and targeted end-user adoption timelines. PHASE III DUAL USE APPLICATIONS: For Phase III, military applications include: - Deploy the ASCN across USSF logistics operations, enabling fully autonomous, AI-enhanced cargo handling at the SJMC and other forward logistics nodes. - Integrate with DoD logistics ecosystems, including USTRANSCOM, SSC, and the DLA, to support seamless multi-domain cargo movement. - Provide real-time logistics decision support for Joint Logistics planners, enhancing resilience in contested or degraded environments. - Improve sustainment for Agile Combat Employment (ACE) and distributed operations through predictive logistics automation and adaptive cargo routing. - Expand use for mission rehearsal and planning through its integration with the Spaceport of the Future Common Operating Picture (COP) Logistics Module. Commercial applications include: - Offer autonomous cargo handling and warehouse robotics solutions to the aerospace and commercial space launch sectors. - Enable AI-driven logistics optimization for commercial supply chains, launch support, and intermodal transport hubs. - Deliver cybersecure, AI-managed inventory and transport systems to spaceports, research facilities, and commercial space cargo operators. - Position the system for future use in lunar and planetary supply chain networks requiring autonomous off-Earth logistics solutions. Transition plan considerations include: - Military Transition through operational implementation at SSC logistics nodes and USTRANSCOM-managed facilities, with support from DLA for broad sustainment integration. - Commercial Licensing to logistics automation firms, aerospace manufacturers, and spaceport operators, supported by targeted pilot deployments. - Technology Integration with enterprise AI/machine learning (ML) platforms used in military logistics and commercial warehouse management systems. The anticipated Technology Readiness Level (TRL) for each phase is the following: - Phase I: TRL 3 to 4 Analytical and laboratory-based proof of concept - Phase II: TRL 5 to 6 System/subsystem prototype demonstrated in relevant environment - Phase III: TRL 7 to 9 System demonstration in operational environment and full deployment. REFERENCES: U.S. Space Force. (2023, March). Mission sustainment strategy. Office of the Deputy Chief of Space Operations for Operations, Cyber, and Nuclear (SF/S4O). https://www.dau.edu/sites/default/files/webform/documents/26816/2023_%20USSF%2Mission%20Sustainment%20Strategy%20efile_signatures.pdf. United States Space Force. (2022, December). Space Doctrine Publication 4-0: Sustainment. Space Training and Readiness Command (STARCOM). https://www.starcom.spaceforce.mil/Portals/2/SDP%2040%20Sustainment%20(Signed).pdf?ver=jFc_4BiAkDjJdc49LmESgg%3D%3D. KEYWORDS: Autonomous Cargo Logistics for Space; AI-Driven Cargo Management System; Autonomous Space Mobility & Sustainment; Digital Twin for Space Logistics Optimization; Cybersecure AI Logistics Framework
