ComplementaryFilter.h

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/*
  @author Roberto G. Valenti <robertogl.valenti@gmail.com>
        @section LICENSE
  Copyright (c) 2015, City University of New York
  CCNY Robotics Lab <http://robotics.ccny.cuny.edu>
        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 City College of New York 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 CCNY ROBOTICS LAB BE LIABLE FOR ANY
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*/


#ifndef CORELIB_SRC_IMUFILTER_COMPLEMENTARYFILTER_H_
#define CORELIB_SRC_IMUFILTER_COMPLEMENTARYFILTER_H_

#include <rtabmap/core/IMUFilter.h>

namespace rtabmap {

class ComplementaryFilter : public IMUFilter
{
  public:
    ComplementaryFilter(const ParametersMap & parameters = ParametersMap());
    virtual ~ComplementaryFilter() {}

    bool setGainAcc(double gain);
    double getGainAcc() const;

    bool setBiasAlpha(double bias_alpha);
    double getBiasAlpha() const;

    // When the filter is in the steady state, bias estimation will occur (if the
    // parameter is enabled).
    bool getSteadyState() const;

    void setDoBiasEstimation(bool do_bias_estimation);
    bool getDoBiasEstimation() const;

    void setDoAdaptiveGain(bool do_adaptive_gain);
    bool getDoAdaptiveGain() const;

    double getAngularVelocityBiasX() const;
    double getAngularVelocityBiasY() const;
    double getAngularVelocityBiasZ() const;

    virtual void parseParameters(const ParametersMap & parameters);
    virtual IMUFilter::Type type() const {return IMUFilter::kComplementaryFilter;}
        virtual void getOrientation(double & qx, double & qy, double & qz, double & qw) const;
        virtual void reset(double qx = 0.0, double qy = 0.0, double qz = 0.0, double qw = 1.0);

    // Update from accelerometer and gyroscope data.
    // [gx, gy, gz]: Angular veloctiy, in rad / s.
    // [ax, ay, az]: Normalized gravity vector.
    // dt: time delta, in seconds.
    virtual void updateImpl(
                double gx, double gy, double gz,
                        double ax, double ay, double az,
            double dt);

  private:
    static const double kGravity;
    static const double gamma_;
    // Bias estimation steady state thresholds
    static const double kAngularVelocityThreshold;
    static const double kAccelerationThreshold;
    static const double kDeltaAngularVelocityThreshold;

    // Gain parameter for the complementary filter, belongs in [0, 1].
    double gain_acc_;

    // Bias estimation gain parameter, belongs in [0, 1].
    double bias_alpha_;

    // Parameter whether to do bias estimation or not.
    bool do_bias_estimation_;

    // Parameter whether to do adaptive gain or not.
    bool do_adaptive_gain_;

    bool initialized_;
    bool steady_state_;

    // The orientation as a Hamilton quaternion (q0 is the scalar). Represents
    // the orientation of the fixed frame wrt the body frame.
    double q0_, q1_, q2_, q3_;

    // Bias in angular velocities;
    double wx_prev_, wy_prev_, wz_prev_;

    // Bias in angular velocities;
    double wx_bias_, wy_bias_, wz_bias_;

    void updateBiases(double ax, double ay, double az,
                      double wx, double wy, double wz);

    bool checkState(double ax, double ay, double az,
                    double wx, double wy, double wz) const;

    void getPrediction(
        double wx, double wy, double wz, double dt,
        double& q0_pred, double& q1_pred, double& q2_pred, double& q3_pred) const;

    void getMeasurement(
        double ax, double ay, double az,
        double& q0_meas, double& q1_meas, double& q2_meas, double& q3_meas);

    void getMeasurement(
        double ax, double ay, double az,
        double mx, double my, double mz,
        double& q0_meas, double& q1_meas, double& q2_meas, double& q3_meas);

    void getAccCorrection(
        double ax, double ay, double az,
        double p0, double p1, double p2, double p3,
        double& dq0, double& dq1, double& dq2, double& dq3);

    double getAdaptiveGain(double alpha, double ax, double ay, double az);
};

// Utility math functions:

void normalizeVector(double& x, double& y, double& z);

void normalizeQuaternion(double& q0, double& q1, double& q2, double& q3);

void scaleQuaternion(double gain,
                     double& dq0, double& dq1, double& dq2, double& dq3);

void invertQuaternion(
    double q0, double q1, double q2, double q3,
    double& q0_inv, double& q1_inv, double& q2_inv, double& q3_inv);

void quaternionMultiplication(double p0, double p1, double p2, double p3,
                              double q0, double q1, double q2, double q3,
                              double& r0, double& r1, double& r2, double& r3);

void rotateVectorByQuaternion(double x, double y, double z,
                              double q0, double q1, double q2, double q3,
double& vx, double& vy, double& vz);

}


#endif /* CORELIB_SRC_IMUFILTER_COMPLEMENTARYFILTER_H_ */