Concurrent Technical Session 5C-1: Lean-Manning Feasibility for the Future Canadian Corvette via an Adaptive Ship Operations Core (ASOC)

Lean-Manning Feasibility for the Future Canadian Corvette via an Adaptive Ship Operations Core (ASOC) Prepared for presentation at the Mari-Tech 2026 Conference, Victoria BC. The Royal Canadian Navy (RCN) faces ongoing challenges in recruiting and retaining qualified personnel as several new ship classes advance through planning and production. This highlights the need to explore ways to optimize crew utilization and reduce onboard workload through automation, intelligent decision support, and AI integration. The proposed Adaptive Ship Operations Core (ASOC) offers a structured approach to evaluate how enhanced data integration, predictive analytics, and supervised autonomy can safely optimize crew requirements. The upcoming Continental Defence Corvette (CDC) serves as a reference platform to examine how these capabilities could enable safe and efficient operation with fewer personnel while maintaining readiness and resilience. ASOC represents a high-level evolution of traditional Integrated Platform Management Systems (IPMS) into adaptive, AI-enabled environments that augment human decision-making and operational control. Acting as a unifying layer, it enhances IPMS through intelligent data processing, contextual assistance, and adaptive workflows. Rather than relying on static checklists or manual monitoring, ASOC dynamically interprets ship status, prioritizes actions, and assists the crew in maintaining safety, performance, and mission readiness. Through data fusion, natural-language interaction, and predictive models, it transforms ship information into actionable insights and context-aware recommendations essential for lean-manned and semi-autonomous operations.

Key enablers include:

• AI-assisted decision support and natural-language interaction
• Predictive and physics-based modeling for condition awareness
• Vision and voice-based data inputs for rapid event recognition
• Workflow orchestration for cross-departmental coordination
• Progressive, supervised autonomy Building on L3Harris’s long-standing role as IPMS supplier for RCN platforms, this study outlines how ASOC concepts can support the CDC and extend to other existing and future RCN platforms, providing a scalable path toward intelligent, adaptive, and manpower-efficient fleet operations.

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Concurrent Technical Session 5C-2: Uncrewed Surface Vehicles

Uncrewed surface vehicles (USVs) of various sizes are now used to accomplish several missions traditionally performed by crewed vessels. These range from sea-floor surveys to maritime domain awareness to carrying cargo. Being able to automate these operations, as well as enabling a single operator to run multiple vehicles at once, is part of a growing trend in both autonomy as well as de-carbonization because many such USVs are fully electric, or wind and wave powered. Regulations for these vehicles, and other marine autonomous surface ships (MASS), is being established by various countries and the IMO as robotic and autonomous ships become more prevalent in operational settings such as coastal waters and harbors. Understanding the potential improvements, as well as the many issues, incumbent with using these new technologies is key to adoption, and continued safety and security. This talk will review a number of types of MASS as well as the regulatory environment growing around them.