Class Ukf

Inheritance Relationships

Base Type

Class Documentation

class maplab::Ukf : public maplab::FilterBase

Unscented Kalman filter class.

Implementation of an unscenter Kalman filter (UKF). This class derives from FilterBase and overrides the predict() and correct() methods in keeping with the discrete time UKF algorithm. The algorithm was derived from the UKF Wikipedia article at (http://en.wikipedia.org/wiki/Kalman_filter#Unscented_Kalman_filter) …and this paper: J. J. LaViola, Jr., “A comparison of unscented and extended Kalman filtering for estimating quaternion motion,” in Proc. American Control Conf., Denver, CO, June 4–6, 2003, pp. 2435–2440 Obtained here: http://www.cs.ucf.edu/~jjl/pubs/laviola_acc2003.pdf

Public Functions

explicit Ukf(const double alpha, const double kappa, const double beta)

Constructor for the Ukf class.

Parameters

args – [in] - Generic argument container. It is assumed that args[0] constains the alpha parameter, args[1] contains the kappa parameter, and args[2] contains the beta parameter.

~Ukf()

Destructor for the Ukf class.

virtual bool correct(const LocalizationFilterMeasurement &measurement, const std::vector<size_t> &update_vector)

Carries out the correct step in the predict/update cycle.

Parameters

measurement – [in] - The measurement to fuse with our estimate

virtual void predict(const LocalizationFilterPrediction &odom_prediction = LocalizationFilterPrediction())

Carries out the predict step in the predict/update cycle.

Projects the state and error matrices forward using a model of the vehicle’s motion.

Parameters

  • referenceTime – [in] - The time at which the prediction is being made

  • odom_prediction – [in] - The predicted state from the odometry

Protected Attributes

std::vector<Eigen::VectorXd> sigma_points_

The UKF sigma points.

Used to sample possible next states during prediction.

Eigen::MatrixXd weighted_covariance_sqrt_

This matrix is used to generate the sigmaPoints_.

std::vector<double> sigma_state_weights_

The weights associated with each sigma point when generating a new state.

std::vector<double> sigma_covariance_weights_

The weights associated with each sigma point when calculating a predicted estimateErrorCovariance_.

double lambda_

Used in weight generation for the sigma points.