Struct Monte Carlo Localizer &nbsp; Copy item path

impl MonteCarloLocalizer

pub fn new(config: MonteCarloLocalizationConfig) -> Self

Create a new localizer; panics on invalid config.

pub fn try_new(config: MonteCarloLocalizationConfig) -> RoboticsResult<Self>

Create a new validated localizer.

pub fn with_initial_state( initial_state: MCLState, config: MonteCarloLocalizationConfig, ) -> Self

Create with initial state; panics on invalid inputs.

pub fn try_with_initial_state( initial_state: MCLState, config: MonteCarloLocalizationConfig, ) -> RoboticsResult<Self>

Create with validated initial state.

pub fn try_predict_with_control( &mut self, control: &MCLControl, ) -> RoboticsResult<()>

Predict particles with the same motion model as particle_filter.rs.

pub fn try_update_with_observations( &mut self, observations: &MCLMeasurement, ) -> RoboticsResult<()>

Update particle weights with range observations.

pub fn try_step( &mut self, control: &MCLControl, observations: &MCLMeasurement, ) -> RoboticsResult<MCLState>

Full estimation step.

pub fn estimate(&self) -> MCLState

Get estimated state.

pub fn state_2d(&self) -> State2D

Get estimated state as common type.

pub fn particle_count(&self) -> usize

Current number of particles.

Trait Implementations§

impl StateEstimator for MonteCarloLocalizer

type State = Matrix<f64, Const<4>, Const<1>, ArrayStorage<f64, 4, 1>>

State type used by this estimator

type Measurement = Vec<(f64, f64, f64)>

Measurement type used by this estimator

type Control = Matrix<f64, Const<2>, Const<1>, ArrayStorage<f64, 2, 1>>

Control input type

fn predict(&mut self, control: &Self::Control, _dt: f64)

Prediction step

fn update(&mut self, measurement: &Self::Measurement)

Update step with measurement

fn get_state(&self) -> &Self::State

Get current state estimate

fn get_covariance(&self) -> Option<&DMatrix<f64>>

Get current covariance estimate (if applicable)

Auto Trait Implementations§

impl UnwindSafe for MonteCarloLocalizer

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