cba.h

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#ifndef CBA_H_
#define CBA_H_

#include <ANN/ANN.h>
#include <ros/ros.h>
#include <lfd_common/action_complete.h>
#include <lfd_common/state.h>
#include <vector>

#define MAX_DATA_POINTS "~max_data_points"

#define DEFAULT_MAX_POINTS 1024

#define DIST_THRESH_MULT "~dist_thresh_mult"

#define DEFAULT_DIST_MULT 1.5

#define ANN_EPSILON 0

typedef struct
{
  int l;
  double c;
  int db;
} prediction;

typedef struct
{
  int l;
  int db;
  int cnt;
  double thresh;
} conf;

class cba_learner
{
public:
  cba_learner();

  virtual ~cba_learner();

  void step();

private:
  prediction *classify_state();

  double nearest_neighbor();

  double conf_thresh(int l, int db);

  void update_thresholds();

  void state_listener_callback(const lfd_common::state::ConstPtr &msg);

  bool a_complete_callback(lfd_common::action_complete::Request &req, lfd_common::action_complete::Response &resp);

  ros::NodeHandle node; 
  ros::Publisher execute, add_point, change_point; 
  ros::Subscriber state_listener; 
  ros::ServiceClient classify, correction, demonstration; 
  ros::ServiceServer a_complete; 
  float *s, *sc; 
  int s_size, max_pts, pts, a; 
  bool action_complete, autonomous_action; 
  double dist_thresh, dist_mult; 
  std::vector<conf*> conf_thresholds; 
  ANNpointArray ann_data; 
  int32_t *labels; 
};

int main(int argc, char **argv);

#endif