/*
 * Copyright (c) 2014, 2015, 2016, Charles River Analytics, Inc.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 * notice, this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above
 * copyright notice, this list of conditions and the following
 * disclaimer in the documentation and/or other materials provided
 * with the distribution.
 * 3. Neither the name of the copyright holder nor the names of its
 * contributors may be used to endorse or promote products derived
 * from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
 * COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 * POSSIBILITY OF SUCH DAMAGE.
 */

#ifndef ROBOT_LOCALIZATION_UKF_H
#define ROBOT_LOCALIZATION_UKF_H

#include "robot_localization/filter_base.h"

#include <fstream>
#include <vector>
#include <set>
#include <queue>

namespace RobotLocalization
{

//! @brief 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
//!
class Ukf: public FilterBase
{
  public:
    //! @brief Constructor for the Ukf class
    //!
    //! @param[in] args - 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.
    //!
    explicit Ukf(std::vector<double> args);

    //! @brief Destructor for the Ukf class
    //!
    ~Ukf();

    //! @brief Carries out the correct step in the predict/update cycle.
    //!
    //! @param[in] measurement - The measurement to fuse with our estimate
    //!
    void correct(const Measurement &measurement);

    //! @brief 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.
    //!
    //! @param[in] referenceTime - The time at which the prediction is being made
    //! @param[in] delta - The time step over which to predict.
    //!
    void predict(const double referenceTime, const double delta);

  protected:
    //! @brief Computes the weighted covariance and sigma points
    //!
    void generateSigmaPoints();

    //! @brief Carries out the predict step for the posteriori state of a sigma
    //! point.
    //!
    //! Projects the state and error matrices forward using a model of
    //! the vehicle's motion.
    //!
    //! @param[in,out] sigmaPoint - The sigma point (state vector) to project
    //! @param[in] delta - The time step over which to project
    //!
    void projectSigmaPoint(Eigen::VectorXd& sigmaPoint, double delta);

    //! @brief The UKF sigma points
    //!
    //! Used to sample possible next states during prediction.
    //!
    std::vector<Eigen::VectorXd> sigmaPoints_;

    //! @brief This matrix is used to generate the sigmaPoints_
    //!
    Eigen::MatrixXd weightedCovarSqrt_;

    //! @brief The weights associated with each sigma point when generating
    //! a new state
    //!
    std::vector<double> stateWeights_;

    //! @brief The weights associated with each sigma point when calculating
    //! a predicted estimateErrorCovariance_
    //!
    std::vector<double> covarWeights_;

    //! @brief Used in weight generation for the sigma points
    //!
    double lambda_;

    //! @brief Used to determine if we need to re-compute the sigma
    //! points when carrying out multiple corrections
    //!
    bool uncorrected_;
};

}  // namespace RobotLocalization

#endif  // ROBOT_LOCALIZATION_UKF_H