27 CLandmark::~CLandmark() = 
default;
    34     pose.
mean.
x(pose_mean.x);
    35     pose.
mean.
y(pose_mean.y);
    36     pose.
mean.z(pose_mean.z);
    38     pose.
cov(0, 0) = pose_cov_11;
    39     pose.
cov(1, 1) = pose_cov_22;
    40     pose.
cov(2, 2) = pose_cov_33;
    42     pose.
cov(0, 1) = pose.
cov(1, 0) = pose_cov_12;
    43     pose.
cov(0, 2) = pose.
cov(2, 0) = pose_cov_13;
    45     pose.
cov(1, 2) = pose.
cov(2, 1) = pose_cov_23;
    53     pose_mean.x = pose.
mean.
x();
    54     pose_mean.y = pose.
mean.
y();
    55     pose_mean.z = pose.
mean.z();
    57     pose_cov_11 = 
d2f(pose.
cov(0, 0));
    58     pose_cov_22 = 
d2f(pose.
cov(1, 1));
    59     pose_cov_33 = 
d2f(pose.
cov(2, 2));
    60     pose_cov_12 = 
d2f(pose.
cov(0, 1));
    61     pose_cov_13 = 
d2f(pose.
cov(0, 2));
    62     pose_cov_23 = 
d2f(pose.
cov(1, 2));
    65 uint8_t CLandmark::serializeGetVersion()
 const { 
return 4; }
    68     out << features << pose_mean << normal << pose_cov_11 << pose_cov_22
    69         << pose_cov_33 << pose_cov_12 << pose_cov_13 << pose_cov_23 << ID
    70         << timestampLastSeen << seenTimesCount;
    73 void CLandmark::serializeFrom(
    83                 "Importing from this old version is not implemented");
    87             in >> features >> pose_mean >> normal >> pose_cov_11 >>
    88                 pose_cov_22 >> pose_cov_33 >> pose_cov_12 >> pose_cov_13 >>
    89                 pose_cov_23 >> ID >> timestampLastSeen >> seenTimesCount;
 #define THROW_EXCEPTION(msg)
 
#define IMPLEMENTS_SERIALIZABLE(class_name, base, NameSpace)
To be added to all CSerializable-classes implementation files. 
 
CPoint3D mean
The mean value. 
 
int64_t TLandmarkID
The type for the IDs of landmarks. 
 
#define MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(__V)
For use in CSerializable implementations. 
 
float d2f(const double d)
shortcut for static_cast<float>(double) 
 
mrpt::math::CMatrixDouble33 cov
The 3x3 covariance matrix. 
 
This namespace contains representation of robot actions and observations. 
 
double x() const
Common members of all points & poses classes. 
 
Classes for 2D/3D geometry representation, both of single values and probability density distribution...
 
The class for storing "landmarks" (visual or laser-scan-extracted features,...) 
 
Virtual base class for "archives": classes abstracting I/O streams. 
 
mrpt::vision::TStereoCalibResults out
 
A gaussian distribution for 3D points.