687 lines
23 KiB
C++
687 lines
23 KiB
C++
/**
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* GTSAM Wrap Module Definition
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*
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* These are the current classes available through the matlab toolbox interface,
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* add more functions/classes as they are available.
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*
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* Requirements:
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* Classes must start with an uppercase letter
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* Only one Method/Constructor per line
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* Methods can return
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* - Eigen types: Matrix, Vector
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* - C/C++ basic types: string, bool, size_t, int, double, char
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* - void
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* - Any class with which be copied with boost::make_shared()
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* - boost::shared_ptr of any object type
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* Limitations on methods
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* - Parsing does not support overloading
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* - There can only be one method with a given name
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* Arguments to functions any of
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* - Eigen types: Matrix, Vector
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* - Eigen types and classes as an optionally const reference
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* - C/C++ basic types: string, bool, size_t, int, double
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* - Any class with which be copied with boost::make_shared() (except Eigen)
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* - boost::shared_ptr of any object type (except Eigen)
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* Comments can use either C++ or C style, with multiple lines
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* Namespace definitions
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* - Names of namespaces must start with a lowercase letter
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* - start a namespace with "namespace {"
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* - end a namespace with exactly "}///\namespace [namespace_name]", optionally adding the name of the namespace
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* - This ending is not C++ standard, and must contain "}///\namespace" to parse
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* - Namespaces can be nested
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* Namespace usage
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* - Namespaces can be specified for classes in arguments and return values
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* - In each case, the namespace must be fully specified, e.g., "namespace1::namespace2::ClassName"
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* Methods must start with a lowercase letter
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* Static methods must start with a letter (upper or lowercase) and use the "static" keyword
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* Includes in C++ wrappers
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* - By default, the include will be <[classname].h>
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* - All namespaces must have angle brackets: <path>
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* - To override, add a full include statement just before the class statement
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* - An override include can be added for a namespace by placing it just before the namespace statement
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* - Both classes and namespace accept exactly one namespace
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* Overriding type dependency checks
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* - If you are using a class 'OtherClass' not wrapped in this definition file, add "class OtherClass;" to avoid a dependency error
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* - Limitation: this only works if the class does not need a namespace specification
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*/
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/**
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* Status:
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* - TODO: global functions
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* - TODO: default values for arguments
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* - TODO: overloaded functions
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* - TODO: signatures for constructors can be ambiguous if two types have the same first letter
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* - TODO: Handle gtsam::Rot3M conversions to quaternions
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*/
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// Everything is in the gtsam namespace, so we avoid copying everything in
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//using namespace gtsam;
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namespace gtsam {
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//*************************************************************************
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// base
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//*************************************************************************
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//*************************************************************************
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// geometry
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//*************************************************************************
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class Point2 {
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Point2();
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Point2(double x, double y);
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static gtsam::Point2 Expmap(Vector v);
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static Vector Logmap(const gtsam::Point2& p);
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void print(string s) const;
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double x();
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double y();
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Vector localCoordinates(const gtsam::Point2& p);
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gtsam::Point2 compose(const gtsam::Point2& p2);
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gtsam::Point2 between(const gtsam::Point2& p2);
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gtsam::Point2 retract(Vector v);
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};
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class Point3 {
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Point3();
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Point3(double x, double y, double z);
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Point3(Vector v);
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static gtsam::Point3 Expmap(Vector v);
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static Vector Logmap(const gtsam::Point3& p);
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void print(string s) const;
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bool equals(const gtsam::Point3& p, double tol);
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Vector vector() const;
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double x();
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double y();
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double z();
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Vector localCoordinates(const gtsam::Point3& p);
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gtsam::Point3 retract(Vector v);
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gtsam::Point3 compose(const gtsam::Point3& p2);
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gtsam::Point3 between(const gtsam::Point3& p2);
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};
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class Rot2 {
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Rot2();
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Rot2(double theta);
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static gtsam::Rot2 Expmap(Vector v);
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static Vector Logmap(const gtsam::Rot2& p);
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static gtsam::Rot2 fromAngle(double theta);
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static gtsam::Rot2 fromDegrees(double theta);
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static gtsam::Rot2 fromCosSin(double c, double s);
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static gtsam::Rot2 relativeBearing(const gtsam::Point2& d); // Ignoring derivative
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static gtsam::Rot2 atan2(double y, double x);
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void print(string s) const;
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bool equals(const gtsam::Rot2& rot, double tol) const;
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double theta() const;
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double degrees() const;
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double c() const;
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double s() const;
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Vector localCoordinates(const gtsam::Rot2& p);
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gtsam::Rot2 retract(Vector v);
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gtsam::Rot2 compose(const gtsam::Rot2& p2);
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gtsam::Rot2 between(const gtsam::Rot2& p2);
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};
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class Rot3 {
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Rot3();
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Rot3(Matrix R);
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static gtsam::Rot3 Rx(double t);
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static gtsam::Rot3 Ry(double t);
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static gtsam::Rot3 Rz(double t);
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// static gtsam::Rot3 RzRyRx(double x, double y, double z); // FIXME: overloaded functions don't work yet
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static gtsam::Rot3 RzRyRx(Vector xyz);
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static gtsam::Rot3 yaw (double t); // positive yaw is to right (as in aircraft heading)
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static gtsam::Rot3 pitch(double t); // positive pitch is up (increasing aircraft altitude)
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static gtsam::Rot3 roll (double t); // positive roll is to right (increasing yaw in aircraft)
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static gtsam::Rot3 ypr(double y, double p, double r);
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static gtsam::Rot3 quaternion(double w, double x, double y, double z);
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static gtsam::Rot3 rodriguez(Vector v);
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void print(string s) const;
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bool equals(const gtsam::Rot3& rot, double tol) const;
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static gtsam::Rot3 identity();
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gtsam::Rot3 compose(const gtsam::Rot3& p2) const;
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gtsam::Rot3 inverse() const;
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gtsam::Rot3 between(const gtsam::Rot3& p2) const;
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gtsam::Point3 rotate(const gtsam::Point3& p) const;
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gtsam::Point3 unrotate(const gtsam::Point3& p) const;
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gtsam::Rot3 retractCayley(Vector v) const;
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gtsam::Rot3 retract(Vector v) const;
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Vector localCoordinates(const gtsam::Rot3& p) const;
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static gtsam::Rot3 Expmap(Vector v);
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static Vector Logmap(const gtsam::Rot3& p);
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Matrix matrix() const;
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Matrix transpose() const;
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gtsam::Point3 column(int index) const;
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Vector xyz() const;
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Vector ypr() const;
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Vector rpy() const;
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double roll() const;
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double pitch() const;
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double yaw() const;
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// Vector toQuaternion() const; // FIXME: Can't cast to Vector properly
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};
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class Pose2 {
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Pose2();
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Pose2(double x, double y, double theta);
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Pose2(double theta, const gtsam::Point2& t);
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Pose2(const gtsam::Rot2& r, const gtsam::Point2& t);
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Pose2(Vector v);
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static gtsam::Pose2 Expmap(Vector v);
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static Vector Logmap(const gtsam::Pose2& p);
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void print(string s) const;
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bool equals(const gtsam::Pose2& pose, double tol) const;
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double x() const;
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double y() const;
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double theta() const;
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int dim() const;
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Vector localCoordinates(const gtsam::Pose2& p);
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gtsam::Pose2 retract(Vector v);
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gtsam::Pose2 compose(const gtsam::Pose2& p2);
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gtsam::Pose2 between(const gtsam::Pose2& p2);
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gtsam::Rot2 bearing(const gtsam::Point2& point);
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double range(const gtsam::Point2& point);
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gtsam::Point2 translation() const;
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gtsam::Rot2 rotation() const;
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};
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class Pose3 {
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Pose3();
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Pose3(const gtsam::Rot3& r, const gtsam::Point3& t);
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Pose3(Vector v);
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Pose3(Matrix t);
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Pose3(const gtsam::Pose2& pose2);
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static gtsam::Pose3 Expmap(Vector v);
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static Vector Logmap(const gtsam::Pose3& p);
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void print(string s) const;
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bool equals(const gtsam::Pose3& pose, double tol) const;
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double x() const;
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double y() const;
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double z() const;
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Matrix matrix() const;
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Matrix adjointMap() const;
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gtsam::Pose3 compose(const gtsam::Pose3& p2);
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gtsam::Pose3 between(const gtsam::Pose3& p2);
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gtsam::Pose3 retract(Vector v);
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gtsam::Pose3 retractFirstOrder(Vector v);
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gtsam::Point3 translation() const;
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gtsam::Rot3 rotation() const;
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};
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//*************************************************************************
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// inference
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//*************************************************************************
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//*************************************************************************
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// linear
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//*************************************************************************
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class SharedGaussian {
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SharedGaussian(Matrix covariance);
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void print(string s) const;
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};
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class SharedDiagonal {
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SharedDiagonal(Vector sigmas);
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void print(string s) const;
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Vector sample() const;
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};
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class SharedNoiseModel {
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static gtsam::SharedNoiseModel sharedSigmas(Vector sigmas);
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static gtsam::SharedNoiseModel sharedSigma(size_t dim, double sigma);
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static gtsam::SharedNoiseModel sharedPrecisions(Vector precisions);
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static gtsam::SharedNoiseModel sharedPrecision(size_t dim, double precision);
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static gtsam::SharedNoiseModel sharedUnit(size_t dim);
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static gtsam::SharedNoiseModel sharedSqrtInformation(Matrix R);
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static gtsam::SharedNoiseModel sharedCovariance(Matrix covariance);
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void print(string s) const;
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};
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class VectorValues {
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VectorValues();
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VectorValues(int nVars, int varDim);
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void print(string s) const;
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bool equals(const gtsam::VectorValues& expected, double tol) const;
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int size() const;
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void insert(int j, Vector value);
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};
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class GaussianConditional {
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GaussianConditional(int key, Vector d, Matrix R, Vector sigmas);
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GaussianConditional(int key, Vector d, Matrix R, int name1, Matrix S,
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Vector sigmas);
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GaussianConditional(int key, Vector d, Matrix R, int name1, Matrix S,
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int name2, Matrix T, Vector sigmas);
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void print(string s) const;
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bool equals(const gtsam::GaussianConditional &cg, double tol) const;
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};
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class GaussianDensity {
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GaussianDensity(int key, Vector d, Matrix R, Vector sigmas);
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void print(string s) const;
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Vector mean() const;
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Matrix information() const;
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Matrix covariance() const;
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};
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class GaussianBayesNet {
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GaussianBayesNet();
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void print(string s) const;
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bool equals(const gtsam::GaussianBayesNet& cbn, double tol) const;
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void push_back(gtsam::GaussianConditional* conditional);
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void push_front(gtsam::GaussianConditional* conditional);
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};
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class GaussianFactor {
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void print(string s) const;
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bool equals(const gtsam::GaussianFactor& lf, double tol) const;
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double error(const gtsam::VectorValues& c) const;
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};
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class JacobianFactor {
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JacobianFactor();
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JacobianFactor(Vector b_in);
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JacobianFactor(int i1, Matrix A1, Vector b, const gtsam::SharedDiagonal& model);
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JacobianFactor(int i1, Matrix A1, int i2, Matrix A2, Vector b,
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const gtsam::SharedDiagonal& model);
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JacobianFactor(int i1, Matrix A1, int i2, Matrix A2, int i3, Matrix A3,
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Vector b, const gtsam::SharedDiagonal& model);
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void print(string s) const;
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bool equals(const gtsam::GaussianFactor& lf, double tol) const;
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bool empty() const;
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Vector getb() const;
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double error(const gtsam::VectorValues& c) const;
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gtsam::GaussianConditional* eliminateFirst();
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};
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class HessianFactor {
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HessianFactor(const gtsam::HessianFactor& gf);
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HessianFactor();
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HessianFactor(int j, Matrix G, Vector g, double f);
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HessianFactor(int j, Vector mu, Matrix Sigma);
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HessianFactor(int j1, int j2, Matrix G11, Matrix G12, Vector g1, Matrix G22,
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Vector g2, double f);
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HessianFactor(int j1, int j2, int j3, Matrix G11, Matrix G12, Matrix G13,
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Vector g1, Matrix G22, Matrix G23, Vector g2, Matrix G33, Vector g3,
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double f);
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HessianFactor(const gtsam::GaussianConditional& cg);
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HessianFactor(const gtsam::GaussianFactor& factor);
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void print(string s) const;
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bool equals(const gtsam::GaussianFactor& lf, double tol) const;
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double error(const gtsam::VectorValues& c) const;
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};
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class GaussianFactorGraph {
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GaussianFactorGraph();
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GaussianFactorGraph(const gtsam::GaussianBayesNet& CBN);
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// From FactorGraph
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void push_back(gtsam::GaussianFactor* factor);
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void print(string s) const;
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bool equals(const gtsam::GaussianFactorGraph& lfgraph, double tol) const;
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int size() const;
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// Building the graph
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void add(gtsam::JacobianFactor* factor);
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void add(Vector b);
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void add(int key1, Matrix A1, Vector b, const gtsam::SharedDiagonal& model);
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void add(int key1, Matrix A1, int key2, Matrix A2, Vector b,
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const gtsam::SharedDiagonal& model);
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void add(int key1, Matrix A1, int key2, Matrix A2, int key3, Matrix A3,
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Vector b, const gtsam::SharedDiagonal& model);
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void add(gtsam::HessianFactor* factor);
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// error and probability
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double error(const gtsam::VectorValues& c) const;
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double probPrime(const gtsam::VectorValues& c) const;
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// combining
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static gtsam::GaussianFactorGraph combine2(const gtsam::GaussianFactorGraph& lfg1,
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const gtsam::GaussianFactorGraph& lfg2);
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void combine(const gtsam::GaussianFactorGraph& lfg);
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// Conversion to matrices
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Matrix sparseJacobian_() const;
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Matrix denseJacobian() const;
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Matrix denseHessian() const;
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};
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class GaussianSequentialSolver {
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GaussianSequentialSolver(const gtsam::GaussianFactorGraph& graph, bool useQR);
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gtsam::GaussianBayesNet* eliminate() const;
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gtsam::VectorValues* optimize() const;
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gtsam::GaussianFactor* marginalFactor(int j) const;
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Matrix marginalCovariance(int j) const;
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};
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class KalmanFilter {
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KalmanFilter(size_t n);
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gtsam::GaussianDensity* init(Vector x0, const gtsam::SharedDiagonal& P0);
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gtsam::GaussianDensity* init(Vector x0, Matrix P0);
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void print(string s) const;
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static int step(gtsam::GaussianDensity* p);
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gtsam::GaussianDensity* predict(gtsam::GaussianDensity* p, Matrix F, Matrix B, Vector u,
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const gtsam::SharedDiagonal& modelQ);
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gtsam::GaussianDensity* predictQ(gtsam::GaussianDensity* p, Matrix F, Matrix B, Vector u,
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Matrix Q);
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gtsam::GaussianDensity* predict2(gtsam::GaussianDensity* p, Matrix A0, Matrix A1, Vector b,
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const gtsam::SharedDiagonal& model);
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gtsam::GaussianDensity* update(gtsam::GaussianDensity* p, Matrix H, Vector z,
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const gtsam::SharedDiagonal& model);
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gtsam::GaussianDensity* updateQ(gtsam::GaussianDensity* p, Matrix H, Vector z,
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Matrix Q);
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};
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//*************************************************************************
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// nonlinear
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//*************************************************************************
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class Ordering {
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Ordering();
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void print(string s) const;
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bool equals(const gtsam::Ordering& ord, double tol) const;
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void push_back(string key);
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};
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class NonlinearOptimizationParameters {
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NonlinearOptimizationParameters(double absDecrease, double relDecrease,
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double sumError, int iIters, double lambda, double lambdaFactor);
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void print(string s) const;
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};
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}///\namespace gtsam
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//*************************************************************************
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// planarSLAM
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//*************************************************************************
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#include <gtsam/slam/planarSLAM.h>
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namespace planarSLAM {
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class Values {
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Values();
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void print(string s) const;
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gtsam::Pose2 pose(int key) const;
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gtsam::Point2 point(int key) const;
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void insertPose(int key, const gtsam::Pose2& pose);
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void insertPoint(int key, const gtsam::Point2& point);
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};
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class Graph {
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Graph();
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void print(string s) const;
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double error(const planarSLAM::Values& values) const;
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gtsam::Ordering* orderingCOLAMD(const planarSLAM::Values& values) const;
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gtsam::GaussianFactorGraph* linearize(const planarSLAM::Values& values,
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const gtsam::Ordering& ordering) const;
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void addPrior(int key, const gtsam::Pose2& pose, const gtsam::SharedNoiseModel& noiseModel);
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void addPoseConstraint(int key, const gtsam::Pose2& pose);
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void addOdometry(int key1, int key2, const gtsam::Pose2& odometry, const gtsam::SharedNoiseModel& noiseModel);
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void addBearing(int poseKey, int pointKey, const gtsam::Rot2& bearing, const gtsam::SharedNoiseModel& noiseModel);
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void addRange(int poseKey, int pointKey, double range, const gtsam::SharedNoiseModel& noiseModel);
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void addBearingRange(int poseKey, int pointKey, const gtsam::Rot2& bearing, double range,
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const gtsam::SharedNoiseModel& noiseModel);
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Values optimize(const Values& initialEstimate);
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};
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class Odometry {
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Odometry(int key1, int key2, const gtsam::Pose2& measured,
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const gtsam::SharedNoiseModel& model);
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void print(string s) const;
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gtsam::GaussianFactor* linearize(const Values& center, const Ordering& ordering) const;
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};
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class Optimizer {
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Optimizer(planarSLAM::Graph* graph, planarSLAM::Values* values,
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gtsam::Ordering* ordering, gtsam::NonlinearOptimizationParameters* parameters);
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void print(string s) const;
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};
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}///\namespace planarSLAM
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//*************************************************************************
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// gtsam::Pose2SLAM
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//*************************************************************************
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#include <gtsam/slam/pose2SLAM.h>
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namespace pose2SLAM {
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class Values {
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Values();
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void print(string s) const;
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void insertPose(int key, const gtsam::Pose2& pose);
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gtsam::Pose2 pose(int i);
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};
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class Graph {
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Graph();
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void print(string s) const;
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|
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double error(const pose2SLAM::Values& values) const;
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|
gtsam::Ordering* orderingCOLAMD(const pose2SLAM::Values& values) const;
|
|
gtsam::GaussianFactorGraph* linearize(const pose2SLAM::Values& values,
|
|
const gtsam::Ordering& ordering) const;
|
|
|
|
void addPrior(int key, const gtsam::Pose2& pose, const gtsam::SharedNoiseModel& noiseModel);
|
|
void addPoseConstraint(int key, const gtsam::Pose2& pose);
|
|
void addOdometry(int key1, int key2, const gtsam::Pose2& odometry, const gtsam::SharedNoiseModel& noiseModel);
|
|
pose2SLAM::Values optimize(const pose2SLAM::Values& initialEstimate);
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|
};
|
|
|
|
class Optimizer {
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|
Optimizer(pose2SLAM::Graph* graph, pose2SLAM::Values* values,
|
|
gtsam::Ordering* ordering, gtsam::NonlinearOptimizationParameters* parameters);
|
|
void print(string s) const;
|
|
};
|
|
|
|
}///\namespace pose2SLAM
|
|
|
|
//*************************************************************************
|
|
// Simulated2D
|
|
//*************************************************************************
|
|
|
|
#include <gtsam/slam/simulated2D.h>
|
|
namespace simulated2D {
|
|
|
|
class Values {
|
|
Values();
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|
void insertPose(int i, const gtsam::Point2& p);
|
|
void insertPoint(int j, const gtsam::Point2& p);
|
|
int nrPoses() const;
|
|
int nrPoints() const;
|
|
gtsam::Point2 pose(int i);
|
|
gtsam::Point2 point(int j);
|
|
};
|
|
|
|
class Graph {
|
|
Graph();
|
|
};
|
|
|
|
// TODO: add factors, etc.
|
|
|
|
}///\namespace simulated2D
|
|
|
|
// Simulated2DOriented Example Domain
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|
#include <gtsam/slam/simulated2DOriented.h>
|
|
namespace simulated2DOriented {
|
|
|
|
class Values {
|
|
Values();
|
|
void insertPose(int i, const gtsam::Pose2& p);
|
|
void insertPoint(int j, const gtsam::Point2& p);
|
|
int nrPoses() const;
|
|
int nrPoints() const;
|
|
gtsam::Pose2 pose(int i);
|
|
gtsam::Point2 point(int j);
|
|
};
|
|
|
|
class Graph {
|
|
Graph();
|
|
};
|
|
|
|
// TODO: add factors, etc.
|
|
|
|
}///\namespace simulated2DOriented
|
|
|
|
|
|
//// These are considered to be broken and will be added back as they start working
|
|
//// It's assumed that there have been interface changes that might break this
|
|
//
|
|
//class Ordering{
|
|
// Ordering(string key);
|
|
// void print(string s) const;
|
|
// bool equals(const Ordering& ord, double tol) const;
|
|
// Ordering subtract(const Ordering& keys) const;
|
|
// void unique ();
|
|
// void reverse ();
|
|
// void push_back(string s);
|
|
//};
|
|
//
|
|
//class GaussianFactorSet {
|
|
// GaussianFactorSet();
|
|
// void push_back(GaussianFactor* factor);
|
|
//};
|
|
//
|
|
//class Simulated2DPosePrior {
|
|
// Simulated2DPosePrior(Point2& mu, const SharedDiagonal& model, int i);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DValues& c) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOrientedPosePrior {
|
|
// Simulated2DOrientedPosePrior(Pose2& mu, const SharedDiagonal& model, int i);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DOrientedValues& c) const;
|
|
//};
|
|
//
|
|
//class Simulated2DPointPrior {
|
|
// Simulated2DPointPrior(Point2& mu, const SharedDiagonal& model, int i);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DValues& c) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOdometry {
|
|
// Simulated2DOdometry(Point2& mu, const SharedDiagonal& model, int i1, int i2);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DValues& c) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOrientedOdometry {
|
|
// Simulated2DOrientedOdometry(Pose2& mu, const SharedDiagonal& model, int i1, int i2);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DOrientedValues& c) const;
|
|
//};
|
|
//
|
|
//class Simulated2DMeasurement {
|
|
// Simulated2DMeasurement(Point2& mu, const SharedDiagonal& model, int i, int j);
|
|
// void print(string s) const;
|
|
// double error(const Simulated2DValues& c) const;
|
|
//};
|
|
//
|
|
//class GaussianFactor {
|
|
// GaussianFactor(string key1,
|
|
// Matrix A1,
|
|
// Vector b_in,
|
|
// const SharedDiagonal& model);
|
|
// GaussianFactor(string key1,
|
|
// Matrix A1,
|
|
// string key2,
|
|
// Matrix A2,
|
|
// Vector b_in,
|
|
// const SharedDiagonal& model);
|
|
// GaussianFactor(string key1,
|
|
// Matrix A1,
|
|
// string key2,
|
|
// Matrix A2,
|
|
// string key3,
|
|
// Matrix A3,
|
|
// Vector b_in,
|
|
// const SharedDiagonal& model);
|
|
// bool involves(string key) const;
|
|
// Matrix getA(string key) const;
|
|
// pair<Matrix,Vector> matrix(const Ordering& ordering) const;
|
|
// pair<GaussianConditional*,GaussianFactor*> eliminate(string key) const;
|
|
//};
|
|
//
|
|
//class GaussianFactorGraph {
|
|
// GaussianConditional* eliminateOne(string key);
|
|
// GaussianBayesNet* eliminate_(const Ordering& ordering);
|
|
// VectorValues* optimize_(const Ordering& ordering);
|
|
// pair<Matrix,Vector> matrix(const Ordering& ordering) const;
|
|
// VectorValues* steepestDescent_(const VectorValues& x0) const;
|
|
// VectorValues* conjugateGradientDescent_(const VectorValues& x0) const;
|
|
//};
|
|
//
|
|
//class gtsam::Pose2Values{
|
|
// Pose2Values();
|
|
// Pose2 get(string key) const;
|
|
// void insert(string name, const gtsam::Pose2& val);
|
|
// void print(string s) const;
|
|
// void clear();
|
|
// int size();
|
|
//};
|
|
//
|
|
//class gtsam::Pose2Factor {
|
|
// Pose2Factor(string key1, string key2,
|
|
// const gtsam::Pose2& measured, Matrix measurement_covariance);
|
|
// void print(string name) const;
|
|
// double error(const gtsam::Pose2Values& c) const;
|
|
// size_t size() const;
|
|
// GaussianFactor* linearize(const gtsam::Pose2Values& config) const;
|
|
//};
|
|
//
|
|
//class gtsam::pose2SLAM::Graph{
|
|
// pose2SLAM::Graph();
|
|
// void print(string s) const;
|
|
// GaussianFactorGraph* linearize_(const gtsam::Pose2Values& config) const;
|
|
// void push_back(Pose2Factor* factor);
|
|
//};
|
|
//
|
|
//class SymbolicFactor{
|
|
// SymbolicFactor(const Ordering& keys);
|
|
// void print(string s) const;
|
|
//};
|
|
//
|
|
//class Simulated2DPosePrior {
|
|
// GaussianFactor* linearize(const Simulated2DValues& config) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOrientedPosePrior {
|
|
// GaussianFactor* linearize(const Simulated2DOrientedValues& config) const;
|
|
//};
|
|
//
|
|
//class Simulated2DPointPrior {
|
|
// GaussianFactor* linearize(const Simulated2DValues& config) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOdometry {
|
|
// GaussianFactor* linearize(const Simulated2DValues& config) const;
|
|
//};
|
|
//
|
|
//class Simulated2DOrientedOdometry {
|
|
// GaussianFactor* linearize(const Simulated2DOrientedValues& config) const;
|
|
//};
|
|
//
|
|
//class Simulated2DMeasurement {
|
|
// GaussianFactor* linearize(const Simulated2DValues& config) const;
|
|
//};
|
|
//
|
|
//class gtsam::Pose2SLAMOptimizer {
|
|
// Pose2SLAMOptimizer(string dataset_name);
|
|
// void print(string s) const;
|
|
// void update(Vector x) const;
|
|
// Vector optimize() const;
|
|
// double error() const;
|
|
// Matrix a1() const;
|
|
// Matrix a2() const;
|
|
// Vector b1() const;
|
|
// Vector b2() const;
|
|
//};
|