One mission case for the whole team.
Systems engineers, domain specialists, mission designers and operators can work from the same scenario and inspect the same result. That makes disagreements about assumptions visible early.
Collaborative multiphysics co-simulator for space missions
See how the whole mission behaves before you build it.
Turn mission requirements and operational ideas into a connected model you can run, inspect and refine. LunCoSim shows what the mission and system need to do together — before design decisions harden into hardware and procedures.
CONOPS-first — start with mission behavior
AI-ready — agents can act on the mission model
Open source — inspect and adapt the model
Mission-first design
Start with what the mission must do.
Begin with the outcome, the operating sequence and the conditions that could make the plan fail. Then use the model to work out what the system needs to deliver it.
That is the role of CONOPS — a Concept of Operations made concrete. LunCoSim lets you run the sequence, change the conditions and see which capabilities, margins and operator actions the mission requires.
01
Mission requirementsWhat must happen, where, when and under which constraints?
02
CONOPS and behaviorDescribe the sequence, decisions, handoffs and failure responses.
03
Connected mission runLet the system, environment, autonomy and operators interact in one scenario.
04
Engineering decisionsSee what to build, what to change and where the mission is most sensitive.
What collaborative, interactive and co-simulator mean
Three ideas. One practical workflow.
LunCoSim describes how teams use the simulator: work together, explore a live mission and connect the models you already rely on.
Change an assumption and see what follows.
Adjust a command, parameter or scenario and see how the connected system responds. Use the run to investigate a decision while the relevant state is still visible.
Run separate models as one mission study.
LunCoSim coordinates models for vehicle behavior, resources, environment and mission logic in one run. You see how a change in one part affects the mission outcome.
The problem we solve
Test the whole mission, not isolated parts.
A power study can pass while a vehicle still cannot complete its route. A controller can work with ideal sensor data but fail with the data the mission will actually provide. LunCoSim puts those conditions in the same study.
LunCoSim gives the team one mission model it can run. Build the scenario from the parts that affect the outcome: the vehicle, environment, resources, operations and mission rules. Then change one part and see how the rest responds. People, scripts and AI agents can use the same command and observation interface.
What goes into the run
What the run tells you
Mission goals
Environment
Resources
Autonomy
One mission run
Can the plan complete its objective under these conditions?
See resource limits during the mission
When a system demand changes, the battery, bus and thermal state change with it. This keeps resource margins tied to the mission instead of to a separate budget.
Test decisions under the conditions they change
Run the system in its environment and with its available resources. See what the same command or plan achieves when those conditions change.
Let autonomy and AI act on the same mission
A controller or AI agent can read the mission state, choose an action and evaluate the outcome through the same interface used by engineers.
Make the assumptions reviewable
Keep the geometry, behavior and connections visible to the team. The shared OpenUSD scene shows what is in the study and how the parts are connected.
AI agent
observeMission state
chooseActions
compareOutcomes
repeatScenarios
Built for the AI era
Let AI test decisions in the full mission context.
An AI agent is useful to engineering only when it sees the same state and constraints as the team. LunCoSim gives agents a live mission state, defined actions and repeatable scenarios for testing plans and trade-offs.
People, scripts and AI agents interact with the same mission state. An agent's test is therefore part of the study the team is reviewing, not a separate demonstration.
ObserveRead the state that matters across the mission.
ActApply decisions through the same controls as the team.
CompareRun scenarios, test alternatives and inspect outcomes.
Who benefits
Use it when the answer crosses disciplines.
LunCoSim is useful when a mission decision depends on several parts of the system responding together.
Built for
- Mission and systems teams deciding which capabilities a concept needs
- Robotics and autonomy teams testing commands against physical and resource limits
- Design teams comparing vehicle, payload, power, thermal or control options
- Operations teams rehearsing normal and failure procedures
- Developers running repeatable studies from scripts, automated testing or AI agents
Use it alongside
- Specialist solvers when detailed component physics is the decision
- Formal verification and qualification workflows that produce certification evidence
Questions you can explore
Answer the mission question before choosing the system.
Define the outcome first, then include the system behavior that can change it. These are examples of questions the platform can help answer today.
Can the mission plan work from start to finish?
Turn requirements and CONOPS into executable scenarios. Check timing, constraints, handoffs and failure responses before the design is fixed.
What does one decision change elsewhere?
See dynamics, power, thermal behavior, sensing and control respond together instead of validating each discipline in isolation.
Can people or agents execute the mission?
Rehearse procedures, let scripts or AI agents act on live state, compare choices and find the edges of an operating plan.
Does the environment change the answer?
Study the system in the gravity, terrain, lighting and communications context that makes a space mission different from a lab test.
What the platform connects
Connect the models and data your mission needs.
Keep the scene, system behavior, terrain and automation in one study so the team can change an assumption and see its effect.
OpenUSD
Keep geometry, physics, joints, materials and connections readable across the team. OpenUSD is the scene format, not just an export target.
Modelica
Build equation-based models for power, thermal, guidance and propulsion studies. Engineers can inspect the equations and adjust the behavior they are testing.
Terrain data
Test site selection and touchdown on real terrain data, with the location kept attached to the ground the mission will encounter.
Automation and AI interface
Give scripts and AI agents a way to read the mission and send commands through the same interface as other controls.
Mission location and time
Place the mission in the right location and time, using the vehicle and planetary data the study needs.
Designed to grow
Planned ways to connect more of your workflow.
The items below are planned for later releases. They describe where the platform can connect to more engineering and robotics workflows.
Future feature
Model exchange
Bring existing system models into the same mission study through broader FMI and SSP support.
Planned
Future feature
Robotics middleware
Connect robotics software and telemetry to the same mission model through ROS 2 and other adapters.
Planned
Future feature
Systems traceability
Link requirements and system definitions to the simulations and evidence used to verify them.
Planned
Future feature
Test-loop integration
Use the simulator in deeper software-in-the-loop, hardware-in-the-loop and mission-rehearsal workflows.
Planned
Applications
See the same mission-first method in action.
LunCoSim is the platform for exploring complete space missions. Rover and lander studies are two ways to see it in action — the same mission-first approach extends to spacecraft, payloads, surface systems and operations.
Rover mission
Can this rover complete the planned route?
Study mobility, power, thermal margin and autonomy together to see whether the rover can reach its destination with margin.
Rover simulation Lander missionCan this lander land safely at the planned site?
Study guidance, thrust, propellant, vehicle state and terrain together through touchdown.
Lander simulation Other space missionsExplore another space mission.
Use the same approach for spacecraft, payloads, surface systems or mission operations when several models must work together.
Discuss your mission
Make results comparable
Compare designs on the same mission.
Keep the mission question, conditions and outputs consistent, then see which design or operating plan holds up.
Same mission question
Compare options against one objective and one set of conditions.
Repeatable runs
Run the same study by hand, from a script or with an AI agent.
Visible assumptions
See the model and conditions that produced a result.
Open model
Read, adapt and extend the model as your mission changes.
The project includes repeatable checks for the model and runtime boundaries. Read the source and methods on GitHub.
Questions, answered
The short version.
Here are the questions teams usually ask before they start.
What is LunCoSim?
LunCoSim is a collaborative multiphysics co-simulator for space missions. It turns mission behavior into an executable model where system dynamics, subsystem behavior, environment and autonomy can be tested together.
What does CONOPS mean here?
Concept of Operations describes what the mission must accomplish, how people and autonomous systems behave, and what happens when conditions change. LunCoSim lets teams run that behavior before committing to a system design.
What do I gain over separate subsystem studies?
Separate tools can validate individual disciplines. LunCoSim adds the mission context: it runs the system, environment, resources and operations together so teams can see effects that separate studies cannot show.
Is LunCoSim only for lunar missions?
No. LunCoSim is a platform for space-mission design. Rover and lander studies are examples; the same approach can be applied to spacecraft, payloads, surface systems and mission operations.
How can AI use LunCoSim?
AI agents can read the mission state, issue commands, run scenarios and compare outcomes through the same interface used by engineers and scripts. AI uses the simulator as another mission operator.
What can I model today?
Today, LunCoSim supports rigid-body motion, electrical power, thermal behavior, guidance and control, sensors, terrain, and selected propulsion and communications models.
Who is LunCoSim for?
It is for systems engineers, robotics teams, mission designers and operators who need interacting system behavior in one run. It complements specialist analysis by showing how subsystem results affect the mission as a whole.
Start here
Start with the mission question.
Tell us what the mission must accomplish. We can help turn the requirements and CONOPS into a scenario, identify the behavior that can make or break the outcome and scope the next engineering step.