ConfidenceRegionScenario
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.
A Gaussian position estimate with principal standard deviations sigmas: its coverage region against site’s grasp tolerance.
Notes
Equation: result evaluates the configured solver; its contract owns the governing equations.
Assumptions: Principal-axis errors follow the Gaussian geometry assumed by ConfidenceRegionModel.
Excludes: Non-Gaussian tails, covariance estimation, and grasp-success prediction.
References
Derivation: The scenario binds declared inputs to ConfidenceRegionModel. Those implementations document their derivations and sources.
Examples
Execute the registered worked inputs; this is a modeled calculation.
>>> from mlsysim import Scenarios
>>> case = Scenarios.DistantHandleConfidenceRegion
>>> value = case.result
>>> round(value.worst_over_tolerance, 3)
2.236Attributes
| Name | Description |
|---|---|
| coverage | |
| result | Evaluate the configured inputs with mlsysim.solvers.ConfidenceRegionModel.solve. |
| sigmas | |
| site |
site
Type: Any.
Declared default: required.
sigmas
Type: List[Quantity].
Declared default: required.
coverage
Type: float.
Declared default: required.
result
engine.scenario_types.ConfidenceRegionScenario.result
Evaluate the configured inputs with mlsysim.solvers.ConfidenceRegionModel.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 = ConfidenceRegionModel().solve(...) using the fields shown below.