Phase Structure Overview
| Phase | Focus | System State |
|---|---|---|
| Phase 1 | Foundations | Deterministic / Prototype |
| Phase 2 | Labour & Agents | Deterministic / Integrated |
| Phase 3 | Stochastic Logic | Probabilistic / GUI |
| Phase 4 | Advanced Analysis | Hybrid Optimization / Trade-off Analysis |
| Phase 5 | Adaptive Design | Hybrid Optimization / Parametric Design |
| Phase 6+ | Physical Realization | Hybrid Modelling / Embodied AI |
Capability Milestones
VALIDATED
Phase 1 — Foundations
Core Objectives & Deliverables
Objectives
- Define STC architecture and formalize module interface standards.
- Implement early planning algorithms.
Key Deliverables
- Complete STC Documentation and Planning.
- Create example Environments, Modules, and Missions.
- Website & Public Documentation.
ACTIVE PHASE
Phase 2 — Integrated Systems & Agents
Core Objectives & Deliverables
Objectives
- Incorporate labour and agent logic into the core planning loop.
- Refine resource modelling constraints for higher simulation fidelity.
- Decouple environment, module, and mission definitions for high iterability.
Key Deliverables
- Agent and labor logic integrated to the Resource & Logistics Planner.
- Enhanced resource simulation (Corrected Logic).
- Iterable yaml/json files for modules, environments, and missions.
- Expanded user customization of program parameters.
Phase 3 — Stochastic Simulation
Core Objectives & Deliverables
Objectives
- Transition from Deterministic to Stochastic/Probabilistic Models.
- Implement probabilistic failure rates and environmental hazards (e.g., Solar Storms).
- Significantly improve physics engine to reflect realistic constraints.
- Develop a robust GUI for system interaction and visualization.
- Add an extensive error catching framework for enhanced diagnosis.
Key Deliverables
- Monte Carlo Simulation, failure rates, random events, and probabilistic constraints.
- Radiation, geophysical, atmospheric, and energy based physics constraints.
- PySide6 integrated GUI.
- Improved error catching system.
Phase 4 — Analytical Frontiers
Core Objectives & Deliverables
Objectives
- Implement hybrid optimization framework for advanced decision making.
- Incorporate trade, sensitivity, and pareto analysis for improved reasoning.
- Commence development of Planetary Surface Analyser.
Key Deliverables
- Planetary Surface Analyser (Live Pipeline).
- A hybrid optimization system for the Resource & Logistics Planner combining Multi-objective Linear Integer Programming (MOLIP), Stochastic Optimization, Markov Decision Process, Reinforcement Learning, and Dynamic Programming.
- Analysis Engine for Resource & Logistics Planner to create and evaluate alternate solutions using trade, sensitivity, and pareto analysis.
Phase 5 — Adaptive Designs
Core Objectives & Deliverables
Objectives
- Create modules defined by constraint based parameters (e.g., geometry, materials, systems, etc.).
- Development of the Modular Infrastructure Generator to create new module designs based on existing modules.
- Complete completed tests showing the Modular Infrastructure Generator creating new module designs to meet an environment that existing modules couldn't meet.
Key Deliverables
- A Modular Infrastructure Generator able to create new modules.
- Modules defined by an extensive list of constraints and parameters.
- Tests proving successful design adaptation under extreme constraints and varied environments and missions.
Phase 6 — Physical Realization
Core Objectives & Deliverables
Objectives
- Commence development of the Autonomous Constructor & Colony Layout Engine.
- Complete the functional prototype of the Planetary Surface Analyser.
- Create code to CAD (Computer Aided Designs) feature in Modular Infrastructure Generator to generate 3d designs of each module for the Colony Layout Engine.
Key Deliverables
- Pipeline for Colony Layout Engine and mechanical, electrical, and software design of the Autonomous Constructor.
- Finished prototype for the Planetary Surface Analyser system capable of processing orbital images and mapping terrain.
- Geometry & material information to 3d design feature added into Modular Infrastructure Generator.
Academic & Research Alignment
Phases 1-3
Undergraduate Portfolio
Focus on core framework development and the Resource & Logistics Planner.
Phase 4 (Start)
Undergraduate (Core Functions)
Implementation of standard analytical pipelines.
Phase 4 (End)
Honours Research
Advanced hybrid optimization, analysis, and subsystem development.
Phase 5+
Master / PhD Research
Novel contributions to long-horizon autonomous systems and stochastic modeling. Developed physical systems.