About LunCo: Open Space Engineering

Space missions are developed across specialised tools, teams and formats. That separation is useful within individual disciplines, but it makes system-level questions expensive to answer and leaves important assumptions at the boundaries.

• Disconnected engineering workflows: A vehicle, payload, terrain model, power budget and operations plan can each look correct while their interfaces remain untested.
• Assumptions disappear at the boundary: Teams translate files and restate conventions instead of sharing the definitions that produced a result.
• Integration arrives too late: When the complete mission is exercised only after the design is fixed, discovering a cross-domain failure is costly and difficult to trace.

The opportunity is to make system-level engineering more collaborative without hiding the detail that makes a result useful. Open models, shared interfaces and executable scenarios can connect the early trade study to the operational question.

• More systems in the loop: Rovers, landers, payloads, communications and surface infrastructure increasingly affect one another. Their interactions belong in the study, not only in separate spreadsheets.
• Grounded AI workflows: An AI agent can help explore a mission only when it has a connected world with state, constraints, actions and evidence to inspect.
• Reusable engineering knowledge: Shared models and clear interfaces let teams build on previous work while retaining the assumptions and provenance needed for review.
• Standards at the boundaries: Explicit interfaces reduce the translation work that appears whenever a mechanical, electrical, software or operations model changes hands.

Several changes make open space engineering more practical now:

LunCo's ecosystem addresses these layers through three connected projects:

• LunCoSim:An open-source multiphysics mission simulator for connecting system behavior, terrain, control and operations in one inspectable study.
• LORS (Lunar Open Rover Standard):An open robotics standard for making rover interfaces easier to share, test and extend across teams.
• CosmiFi:A planned library of reusable engineering blueprints and mission designs, with the assumptions and interfaces needed to use them in a new study.

• Open-Source First: Core software and interfaces stay available for inspection. Contributors can reproduce a result, propose a change, and review the assumptions in the toolchain.
• Scenario-driven validation: A model becomes useful when it can be run against a mission scenario, compared with another choice and inspected when the result changes.
• Standards-Driven Interoperability: LORS makes rover interfaces explicit, so teams can compare implementations, test conformance, and extend a system without renegotiating every boundary.
• Human and AI participation: People and agents should work through the same mission state and interfaces, with human judgment remaining part of the operating loop.
• Inspectable engineering: Models, interfaces and scenarios should be available for review, so a result can be understood rather than accepted as an unexplained output.