79 lines
1.9 KiB
C++
79 lines
1.9 KiB
C++
/**
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* @file VSLAMFactor.h
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* @brief A Nonlinear Factor, specialized for visual SLAM
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* @author Alireza Fathi
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*/
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#pragma once
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#include "NonlinearFactor.h"
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#include "GaussianFactor.h"
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#include "Cal3_S2.h"
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#include "Testable.h"
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namespace gtsam {
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class VSLAMConfig;
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/**
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* Non-linear factor for a constraint derived from a 2D measurement,
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* i.e. the main building block for visual SLAM.
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*/
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//class VSLAMFactor : public NonlinearFactor<VSLAMConfig>, Testable<NonlinearFactor<VSLAMConfig> >
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class VSLAMFactor : public NonlinearFactor<VSLAMConfig>, Testable<VSLAMFactor>
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{
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private:
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int cameraFrameNumber_, landmarkNumber_;
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std::string cameraFrameName_, landmarkName_;
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Cal3_S2 K_; // Calibration stored in each factor. FD: need to think about this.
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typedef gtsam::NonlinearFactor<VSLAMConfig> ConvenientFactor;
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public:
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typedef boost::shared_ptr<VSLAMFactor> shared_ptr; // shorthand for a smart pointer to a factor
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/**
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* Constructor
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* @param z is the 2 dimensional location of point in image (the measurement)
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* @param sigma is the standard deviation
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* @param cameraFrameNumber is basically the frame number
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* @param landmarkNumber is the index of the landmark
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* @param K the constant calibration
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*/
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VSLAMFactor(const Vector& z, double sigma, int cameraFrameNumber, int landmarkNumber, const Cal3_S2& K);
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/**
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* print
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* @param s optional string naming the factor
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*/
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void print(const std::string& s="VSLAMFactor") const;
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/**
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* equals
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*/
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bool equals(const VSLAMFactor&, double tol=1e-9) const;
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/**
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* predict the measurement
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*/
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Vector predict(const VSLAMConfig&) const;
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/**
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* calculate the error of the factor
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*/
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Vector error_vector(const VSLAMConfig&) const;
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/**
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* linerarization
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*/
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GaussianFactor::shared_ptr linearize(const VSLAMConfig&) const;
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int getCameraFrameNumber() const { return cameraFrameNumber_; }
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int getLandmarkNumber() const { return landmarkNumber_; }
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};
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}
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