odom_estimation.h

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/* Author: Wim Meeussen */
 
#ifndef __ODOM_ESTIMATION__
#define __ODOM_ESTIMATION__
 
// bayesian filtering
#include <bfl/filter/extendedkalmanfilter.h>
#include <bfl/wrappers/matrix/matrix_wrapper.h>
#include <bfl/model/linearanalyticsystemmodel_gaussianuncertainty.h>
#include <bfl/model/linearanalyticmeasurementmodel_gaussianuncertainty.h>
#include <bfl/pdf/analyticconditionalgaussian.h>
#include <bfl/pdf/linearanalyticconditionalgaussian.h>
#include "nonlinearanalyticconditionalgaussianodo.h"
 
// TF
#include <tf/tf.h>
 
// msgs
#include <geometry_msgs/PoseWithCovarianceStamped.h>
 
// log files
#include <fstream>
 
namespace estimation
{
 
class OdomEstimation
{
public:
  OdomEstimation();
 
  virtual ~OdomEstimation();
 
  bool update(bool odom_active, bool imu_active, bool gps_active, bool vo_active, const ros::Time& filter_time, bool& diagnostics_res);
 
  void initialize(const tf::Transform& prior, const ros::Time& time);
 
  bool isInitialized() {return filter_initialized_;};
 
  void getEstimate(MatrixWrapper::ColumnVector& estimate);
 
  void getEstimate(ros::Time time, tf::Transform& estimate);
 
  void getEstimate(ros::Time time, tf::StampedTransform& estimate);
 
  void getEstimate(geometry_msgs::PoseWithCovarianceStamped& estimate);
 
  void addMeasurement(const tf::StampedTransform& meas);
 
  void addMeasurement(const tf::StampedTransform& meas, const MatrixWrapper::SymmetricMatrix& covar);
 
  void setOutputFrame(const std::string& output_frame);
 
  void setBaseFootprintFrame(const std::string& base_frame);
 
private:
  void angleOverflowCorrect(double& a, double ref);
 
  // decompose Transform into x,y,z,Rx,Ry,Rz
  void decomposeTransform(const tf::StampedTransform& trans,
                          double& x, double& y, double&z, double&Rx, double& Ry, double& Rz);
  void decomposeTransform(const tf::Transform& trans,
                          double& x, double& y, double&z, double&Rx, double& Ry, double& Rz);
 
 
  // pdf / model / filter
  BFL::AnalyticSystemModelGaussianUncertainty*            sys_model_;
  BFL::NonLinearAnalyticConditionalGaussianOdo*           sys_pdf_;
  BFL::LinearAnalyticConditionalGaussian*                 odom_meas_pdf_;
  BFL::LinearAnalyticMeasurementModelGaussianUncertainty* odom_meas_model_;
  BFL::LinearAnalyticConditionalGaussian*                 imu_meas_pdf_;
  BFL::LinearAnalyticMeasurementModelGaussianUncertainty* imu_meas_model_;
  BFL::LinearAnalyticConditionalGaussian*                 vo_meas_pdf_;
  BFL::LinearAnalyticMeasurementModelGaussianUncertainty* vo_meas_model_;
  BFL::LinearAnalyticConditionalGaussian*                 gps_meas_pdf_;
  BFL::LinearAnalyticMeasurementModelGaussianUncertainty* gps_meas_model_;
  BFL::Gaussian*                                          prior_;
  BFL::ExtendedKalmanFilter*                              filter_;
  MatrixWrapper::SymmetricMatrix                          odom_covariance_, imu_covariance_, vo_covariance_, gps_covariance_;
 
  // vars
  MatrixWrapper::ColumnVector vel_desi_, filter_estimate_old_vec_;
  tf::Transform filter_estimate_old_;
  tf::StampedTransform odom_meas_, odom_meas_old_, imu_meas_, imu_meas_old_, vo_meas_, vo_meas_old_, gps_meas_, gps_meas_old_;
  ros::Time filter_time_old_;
  bool filter_initialized_, odom_initialized_, imu_initialized_, vo_initialized_, gps_initialized_;
 
  // diagnostics
  double diagnostics_odom_rot_rel_, diagnostics_imu_rot_rel_;
 
  // tf transformer
  tf::Transformer transformer_;
 
  std::string output_frame_;
  std::string base_footprint_frame_;
 
}; // class
 
}; // namespace
 
#endif