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/* Copyright (c) 2012 Patrick Ruoff
*
* Permission to use, copy, modify, and/or distribute this software for any
* purpose with or without fee is hereby granted, provided that the above
* copyright notice and this permission notice appear in all copies.
*/
#pragma once
#include <opencv2/core.hpp>
#include <vector>
//-----------------------------------------------------------------------------
// Calibrates the translation from head to model = t_MH
// by recursive least squares /
// kalman filter in information form with identity noise covariance
// measurement equation when head position = t_CH is fixed:
// (R_CM_k , Id)*(-t_MH, t_CH) = t_CM_k
class TranslationCalibrator
{
public:
TranslationCalibrator(unsigned yaw_rdof, unsigned pitch_rdof, unsigned roll_rdof);
// reset the calibration process
void reset();
// update the current estimate
void update(const cv::Matx33d& R_CM_k, const cv::Vec3d& t_CM_k);
// get the current estimate for t_MH
std::tuple<cv::Vec3f, unsigned> get_estimate();
private:
bool check_bucket(const cv::Matx33d& R_CM_k);
static int get_index(int yaw, int pitch, int roll);
cv::Matx66f P; // normalized precision matrix = inverse covariance
cv::Vec6f y; // P*(-t_MH, t_CH)
using vec = std::vector<unsigned>;
vec used_yaw_poses;
vec used_pitch_poses;
vec used_roll_poses;
static constexpr double yaw_spacing_in_degrees = 2.5;
static constexpr double pitch_spacing_in_degrees = 1.5;
static constexpr double roll_spacing_in_degrees = 3.5;
unsigned yaw_rdof, pitch_rdof, roll_rdof, nsamples;
};
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