SensorBiasDriftScenario
Robotics scenarios · Implementation: mlsysim/engine/scenario_definitions/robotics/estimation.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
A steady reading whose sensor bias drifts at drift_rate for span, while the estimator reports reported_sigma.
Notes
Equation: result evaluates the configured solver; its contract owns the governing equations.
Assumptions: Bias drifts at a constant supplied rate for the specified span.
Excludes: A full estimator update; reported_sigma and excitation do not enter result.
References
Derivation: The scenario binds declared inputs to SensorBiasDriftModel. Those implementations document their derivations and sources.
Examples
Execute the registered worked inputs; this is a modeled calculation.
>>> from mlsysim import Scenarios
>>> case = Scenarios.WristForceBiasDrift
>>> value = case.result
>>> print(f"{value.shift:.3f~P}")
3.000 NAttributes
| Name | Description |
|---|---|
| drift_rate | |
| excitation | |
| reading | |
| reported_sigma | |
| result | Evaluate the configured inputs with mlsysim.solvers.SensorBiasDriftModel.solve. |
| span |
reading
Type: Quantity.
Declared default: required.
reported_sigma
Type: Quantity.
Declared default: required.
drift_rate
Type: Quantity.
Declared default: required.
span
Type: Quantity.
Declared default: required.
excitation
Type: Optional[Quantity].
Declared default: None.
result
engine.scenario_types.SensorBiasDriftScenario.result
Evaluate the configured inputs with mlsysim.solvers.SensorBiasDriftModel.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 = SensorBiasDriftModel().solve(...) using the fields shown below.