gtsam/cpp/NonlinearConstraint.h

262 lines
8.4 KiB
C++

/*
* @file NonlinearConstraint.h
* @brief Implements nonlinear constraints that can be linearized and
* inserted into an existing nonlinear graph and solved via SQP
* @author Alex Cunningham
*/
#pragma once
#include <map>
#include <boost/function.hpp>
#include "NonlinearFactor.h"
namespace gtsam {
/** Typedef for Lagrange key type - must be present in factors and config */
typedef TypedSymbol<Vector, 'L'> LagrangeKey;
/**
* Base class for nonlinear constraints
* This allows for both equality and inequality constraints,
* where equality constraints are active all the time (even slightly
* nonzero constraint functions will still be active - inequality
* constraints should be sure to force to actual zero)
*
* The measurement z in the underlying NonlinearFactor is the
* set of Lagrange multipliers.
*
* Note on NoiseModel:
* The nonlinear constraint actually uses a Unit noisemodel so that
* it is possible to have a finite error value when the constraint is
* not fulfilled. Using a constrained noisemodel will immediately cause
* infinite error and break optimization.
*/
template <class Config>
class NonlinearConstraint : public NonlinearFactor<Config> {
protected:
/** key for the lagrange multipliers */
LagrangeKey lagrange_key_;
/** number of lagrange multipliers */
size_t p_;
/** type of constraint */
bool isEquality_;
public:
/** Constructor - sets the cost function and the lagrange multipliers
* @param lagrange_key is the label for the associated lagrange multipliers
* @param dim_lagrange is the number of associated constraints
* @param isEquality is true if the constraint is an equality constraint
*/
NonlinearConstraint(const LagrangeKey& lagrange_key,
size_t dim_lagrange,
bool isEquality=true);
/** returns the key used for the Lagrange multipliers */
LagrangeKey lagrangeKey() const { return lagrange_key_; }
/** returns the number of lagrange multipliers */
size_t nrConstraints() const { return p_; }
/** returns the type of constraint */
bool isEquality() const { return isEquality_; }
/** Print */
virtual void print(const std::string& s = "") const =0;
/** Check if two factors are equal */
virtual bool equals(const Factor<Config>& f, double tol=1e-9) const=0;
/** error function - returns the result of the constraint function */
virtual Vector unwhitenedError(const Config& c) const=0;
/**
* Determines whether the constraint is active given a particular configuration
* @param config is the input to the g(x) function
* @return true if constraint needs to be linearized
*/
bool active(const Config& config) const;
/**
* Real linearize, given a config that includes Lagrange multipliers
* @param config is the configuration (with lagrange multipliers)
* @return a combined linear factor containing both the constraint and the constraint factor
*/
virtual boost::shared_ptr<GaussianFactor> linearize(const Config& c) const=0;
};
/**
* A unary constraint with arbitrary cost and jacobian functions
* This is an example class designed for easy testing, but real uses should probably
* subclass NonlinearConstraint and implement virtual functions directly
*/
template <class Config, class Key, class X>
class NonlinearConstraint1 : public NonlinearConstraint<Config> {
private:
/**
* Calculates the jacobian of the constraint function
* returns a pxn matrix
* Use boost.bind to create the function object
* @param config to use for linearization
* @return the jacobian of the constraint in terms of key
*/
boost::function<Matrix(const Config& config)> G_;
/** calculates the constraint function of the current config
* If the value is zero, the constraint is not active
* Use boost.bind to create the function object
* @param config is a configuration of all the variables
* @return the cost for each of p constraints, arranged in a vector
*/
boost::function<Vector(const Config& config)> g_;
/** key for the constrained variable */
Key key_;
public:
/**
* Basic constructor
* @param key is the identifier for the variable constrained
* @param G gives the jacobian of the constraint function
* @param g is the constraint function
* @param dim_constraint is the size of the constraint (p)
* @param lagrange_key is the identifier for the lagrange multiplier
* @param isEquality is true if the constraint is an equality constraint
*/
NonlinearConstraint1(
Vector (*g)(const Config& config),
const Key& key,
Matrix (*G)(const Config& config),
size_t dim_constraint,
const LagrangeKey& lagrange_key,
bool isEquality=true);
/**
* Basic constructor with boost function pointers
* @param key is the identifier for the variable constrained
* @param G gives the jacobian of the constraint function
* @param g is the constraint function as a boost function pointer
* @param dim_constraint is the size of the constraint (p)
* @param lagrange_key is the identifier for the lagrange multiplier
* @param isEquality is true if the constraint is an equality constraint
*/
NonlinearConstraint1(
boost::function<Vector(const Config& config)> g,
const Key& key,
boost::function<Matrix(const Config& config)> G,
size_t dim_constraint,
const LagrangeKey& lagrange_key,
bool isEquality=true);
/** Print */
void print(const std::string& s = "") const;
/** Check if two factors are equal */
bool equals(const Factor<Config>& f, double tol=1e-9) const;
/** Error function */
virtual inline Vector unwhitenedError(const Config& c) const { return g_(c); }
/**
* Linearize from config - must have Lagrange multipliers
*/
virtual boost::shared_ptr<GaussianFactor> linearize(const Config& c) const;
};
/**
* A binary constraint with arbitrary cost and jacobian functions
*/
template <class Config, class Key1, class X1, class Key2, class X2>
class NonlinearConstraint2 : public NonlinearConstraint<Config> {
private:
/**
* Calculates the jacobians of the constraint function in terms of
* the first and second variables
* returns a pxn matrix
* @param config to use for linearization
* @return the jacobian of the constraint in terms of key
*/
boost::function<Matrix(const Config& config)> G1_;
boost::function<Matrix(const Config& config)> G2_;
/** calculates the constraint function of the current config
* If the value is zero, the constraint is not active
* Use boost.bind to create the function object
* @param config is a configuration of all the variables
* @return the cost for each of p constraints, arranged in a vector
*/
boost::function<Vector(const Config& config)> g_;
/** keys for the constrained variables */
Key1 key1_;
Key2 key2_;
public:
/**
* Basic constructor
* @param key is the identifier for the variable constrained
* @param G gives the jacobian of the constraint function
* @param g is the constraint function
* @param dim_constraint is the size of the constraint (p)
* @param lagrange_key is the identifier for the lagrange multiplier
* @param isEquality is true if the constraint is an equality constraint
*/
NonlinearConstraint2(
Vector (*g)(const Config& config),
const Key1& key1,
Matrix (*G1)(const Config& config),
const Key2& key2,
Matrix (*G2)(const Config& config),
size_t dim_constraint,
const LagrangeKey& lagrange_key,
bool isEquality=true);
/**
* Basic constructor with direct function objects
* Use boost.bind to construct the function objects
* @param key is the identifier for the variable constrained
* @param G gives the jacobian of the constraint function
* @param g is the constraint function
* @param dim_constraint is the size of the constraint (p)
* @param lagrange_key is the identifier for the lagrange multiplier
* @param isEquality is true if the constraint is an equality constraint
*/
NonlinearConstraint2(
boost::function<Vector(const Config& config)> g,
const Key1& key1,
boost::function<Matrix(const Config& config)> G1,
const Key2& key2,
boost::function<Matrix(const Config& config)> G2,
size_t dim_constraint,
const LagrangeKey& lagrange_key,
bool isEquality=true);
/** Print */
void print(const std::string& s = "") const;
/** Check if two factors are equal */
bool equals(const Factor<Config>& f, double tol=1e-9) const;
/** Error function */
virtual inline Vector unwhitenedError(const Config& c) const { return g_(c); }
/**
* Linearize from config - must have Lagrange multipliers
*/
virtual boost::shared_ptr<GaussianFactor> linearize(const Config& c) const;
};
}