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Mindpool LabsThe research arm of Mindpool
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Power- and thermal-constrained autonomy

Planned open co-design tooling for autonomous space systems that carries energy and heat rejection as first-class constraints.

EnergyRoboticsSoftware

Before the lunar-night boundary, the lunar rover's solar deck is warm; afterward, it cools. The radiator and internal battery and avionics nodes remain warm, while the wheels remain cold. The display shows energy reserve, battery node temperature, heater demand, and useful work.

The reference mission gives one planner four coupled states: useful work must fall as required to preserve battery charge and component temperatures through the lunar-night boundary.

In many autonomous spacecraft and robots, two groups of engineers share one problem without working from the same state. Power and thermal engineers keep batteries charged and components inside their temperature limits. Autonomy engineers decide what the system does next. Fixed budgets and design margins carry the coupling because the may not see how battery and thermal state change as it moves work through time.

This initiative examines what changes when the planner can see those states directly, through physics models fast enough to run inside the . The objective is not to remove prudent . It is to measure when margin is being consumed, when some of it can be allocated to useful work, and when the system must preserve it.


One primary proof, followed by transfer tests

The primary proof is : lunar-night survival for a representative small rover. Before sunset, the rover must decide how much useful work to complete, how much energy to store, and how to schedule heater loads as illumination falls. The planner succeeds only if it keeps battery state and modeled node temperatures inside their declared limits across the full uncertainty set.

, , and a high-power spacecraft payload remain transfer cases. They share the coupling between scheduled work, stored energy, and , but they introduce different time scales and operating limits. We will test them after the lunar reference result establishes which parts of the model and planner contract are general.

This sequence matters. One reference mission can produce a result that is clear enough to challenge, reproduce, or reject; four simultaneous demonstrations cannot.


The research question

On a small-rover reference mission built from published parameters, does a planner using coupled battery and thermal state complete more useful work than a without violating temperature, state-of-charge, runtime, or uncertainty limits?

That question separates into four claims.

Feasibility

A coupled planner can keep the modeled rover within its battery and thermal limits through the mission horizon.

Operational value

Under the same hardware, initial state, and environment, it can complete more useful activity or preserve a higher probability of survival than the fixed-budget baseline.

Planning performance

The physics model and can return a decision within the declared planning deadline, with deadline misses reported rather than hidden.

Transfer

The model and planner contracts can be reused for later servicing and high-power cases, although the policy, parameters, and validation evidence will change.

We will report survival to the target time, useful activity completed, minimum , minimum and maximum node temperature, solver runtime, deadline misses, and the count and magnitude of . Results will include sensitivity across the published uncertainty range.


What we are building

The initiative is organized as a five-module reference architecture, planned for release under .

Models

Solar generation, battery state, bus losses, component heat loads, and a with conduction, radiation, and rejection. Each model will have a plain and, where speed matters, an optimized fast path tested against it.

Environment

Orbit and , , lunar surface illumination and thermal boundary. An analytic backend will come first, and an interface to established dynamics simulators such as is planned behind it.

Planners

A duty-cycle scheduler will be formulated as a , followed by a controller with and a learned policy as a baseline for comparison.

Simulator

A closed-loop scenario runner will couple the three modules above and be reproducible from a single file and a seed.

Benchmark

Reference Mission 01, its metrics, uncertainty set, and fixed-budget baseline will come first. In-orbit servicing under eclipse, laser against a radiator limit, and a small satellite with a high-power payload will follow as transfer cases.

Five modules connect models, environment, and planners to a closed-loop simulator and benchmark. Solvers feed the models and planners, while the simulator returns state to the planners.

Scroll horizontally to inspect the full diagram.

The fast path is the reason the architecture exists: the solvers sit beneath the models and the planner's inner loop, which is what lets physics-grade constraints run inside the planning loop rather than alongside it.

Evidence gates

Reference definition

Evidence required

Published mission assumptions, parameter sources, uncertainty ranges, metrics, and fixed-budget baseline

Analytical result

Evidence required

Model checks against reference cases, comparison with the baseline, and reported constraint or deadline violations

Independent reproduction

Evidence required

A clean run by a team outside Mindpool using the published scenario and release

Relevant-environment test

Evidence required

The same claims tested on a battery, heater, and radiator breadboard at a partner facility

The specifications will record public interfaces and assumptions while the model and baseline develop. A survey paper will establish the vocabulary; the lunar reference result will test the first claim. Later papers address transfer to servicing, faster thermal , independent runs, and validation. Each paper is planned to include the code and inputs required to reproduce its result. Review the research program


Research software boundary

The benchmark will record units, model fidelity, agreement tolerances, solver deadlines, and every observed constraint violation. These planned releases will support research and design studies. They will not be flight-qualified control software; a vehicle program would require independent qualification, vehicle-specific verification, and its own safety review.


Status

Specifications (RFC-001 to RFC-006)

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In progress

Survey paper

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In progress

Reference Mission 01 definition

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In progress

Fixed-budget baseline

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Planned

Analytical benchmark

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Planned

External benchmark runs

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Planned

Transfer cases

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Planned

Hardware-in-the-loop validation

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Planned

Who we are looking for

We are looking for thermal engineers who can challenge the rover model, autonomy researchers who can challenge the baseline, and organizations that can review a realistic surface scenario before the reference mission is fixed. Servicing and high-power scenarios remain welcome as transfer cases. View open roles · Propose a scenario

The initiative brings energy and heat into the decision without pretending uncertainty has disappeared. If the result holds, a small mission gains greater latitude to use its available hardware while preserving the limits that keep it alive.