IntentLeaseExpiryScenario

Robotics scenarios · Implementation: mlsysim/engine/scenario_definitions/robotics/grounding.py.

Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.

The intent lease for the cadence scenario’s target: its evidence horizons, an administrative_lease, and the stopping deadline from clearance at the TCP speed ceiling, with the arm’s credible deceleration from its handbook worst-case stop.

Notes

Equation: result evaluates the configured solver; its contract owns the governing equations.

Assumptions: The existing cadence horizons and configured stop timing constrain one administrative lease.

Excludes: Actuator identification, changing braking capability, and safety certification.

References

Derivation: The scenario binds declared inputs to IntentLeaseExpiryModel. Those implementations document their derivations and sources.

Examples

Execute the registered worked inputs; this is a modeled calculation.

>>> from mlsysim import Scenarios
>>> case = Scenarios.ConveyorMugIntentLeaseExpiry
>>> value = case.result
>>> print(f"{value.expiry_tracked:.3f~P}")
100.000 ms

Attributes

Name	Description
administrative_lease
cadence
clearance
result	Evaluate the configured inputs with mlsysim.solvers.IntentLeaseExpiryModel.solve.

cadence

Type: IntentCadenceScenario.

Declared default: required.

administrative_lease

Type: Quantity.

Declared default: required.

clearance

Type: Quantity.

Declared default: required.

result

engine.scenario_types.IntentLeaseExpiryScenario.result

Evaluate the configured inputs with mlsysim.solvers.IntentLeaseExpiryModel.solve.

The returned typed result retains the solver’s documented units, assumptions, and feasibility semantics; this property adds no measurement or safety claim. Equation: result = IntentLeaseExpiryModel().solve(...) using the fields shown below.