Abstract class for cost models. More...

#include <cost-base.hpp>

Inheritance diagram for CostModelAbstractTpl< _Scalar >:

Public Types
typedef ActivationModelAbstractTpl< Scalar >	ActivationModelAbstract

typedef ActivationModelQuadTpl< Scalar >	ActivationModelQuad

typedef CostDataAbstractTpl< Scalar >	CostDataAbstract

typedef DataCollectorAbstractTpl< Scalar >	DataCollectorAbstract

typedef MathBaseTpl< Scalar >	MathBase

typedef MathBase::MatrixXs	MatrixXs

typedef ResidualModelAbstractTpl< Scalar >	ResidualModelAbstract

typedef StateAbstractTpl< Scalar >	StateAbstract

typedef MathBase::VectorXs	VectorXs

Public Member Functions
	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, const std::size_t nr)

	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, const std::size_t nr, const std::size_t nu)

	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, std::shared_ptr< ActivationModelAbstract > activation)

	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, std::shared_ptr< ActivationModelAbstract > activation, const std::size_t nu)
	Initialize the cost model. More...

	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, std::shared_ptr< ActivationModelAbstract > activation, std::shared_ptr< ResidualModelAbstract > residual)
	Initialize the cost model. More...

	CostModelAbstractTpl (std::shared_ptr< StateAbstract > state, std::shared_ptr< ResidualModelAbstract > residual)

virtual void	calc (const std::shared_ptr< CostDataAbstract > &data, const Eigen::Ref< const VectorXs > &x)
	Compute the total cost value for nodes that depends only on the state. More...

virtual void	calc (const std::shared_ptr< CostDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0
	Compute the cost value and its residual vector. More...

virtual void	calcDiff (const std::shared_ptr< CostDataAbstract > &data, const Eigen::Ref< const VectorXs > &x)
	Compute the Jacobian and Hessian of the cost functions with respect to the state only. More...

virtual void	calcDiff (const std::shared_ptr< CostDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0
	Compute the Jacobian and Hessian of cost and its residual vector. More...

virtual std::shared_ptr< CostDataAbstract >	createData (DataCollectorAbstract *const data)
	Create the cost data. More...

const std::shared_ptr< ActivationModelAbstract > &	get_activation () const
	Return the activation model.

std::size_t	get_nu () const
	Return the dimension of the control input.

template<class ReferenceType >
ReferenceType	get_reference ()
	Return the cost reference.

const std::shared_ptr< ResidualModelAbstract > &	get_residual () const
	Return the residual model.

const std::shared_ptr< StateAbstract > &	get_state () const
	Return the state.

virtual void	print (std::ostream &os) const
	Print relevant information of the cost model. More...

template<class ReferenceType >
void	set_reference (ReferenceType ref)
	Modify the cost reference.

Public Attributes
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef _Scalar	Scalar

Protected Member Functions
virtual void	get_referenceImpl (const std::type_info &, void *)
	Return the cost reference.

virtual void	set_referenceImpl (const std::type_info &, const void *)
	Modify the cost reference.

Protected Attributes
std::shared_ptr< ActivationModelAbstract >	activation_
	Activation model.

std::size_t	nu_
	Control dimension.

std::shared_ptr< ResidualModelAbstract >	residual_
	Residual model.

std::shared_ptr< StateAbstract >	state_
	State description.

VectorXs	unone_
	No control vector.

Friends
template<class Scalar >
std::ostream &	operator<< (std::ostream &os, const CostModelAbstractTpl< Scalar > &model)
	Print information on the cost model.

Detailed Description

template<typename _Scalar>
class crocoddyl::CostModelAbstractTpl< _Scalar >

Abstract class for cost models.

A cost model is defined by the scalar activation function \(a(\cdot)\) and by the residual function \(\mathbf{r}(\cdot)\) as follows:

\[ \ell(\mathbf{x},\mathbf{u}) = a(\mathbf{r}(\mathbf{x}, \mathbf{u})), \]

where the residual function depends on the state point \(\mathbf{x}\in\mathcal{X}\), which lies in the state manifold described with a nx-tuple, its velocity \(\dot{\mathbf{x}}\in T_{\mathbf{x}}\mathcal{X}\) that belongs to the tangent space with ndx dimension, and the control input \(\mathbf{u}\in\mathbb{R}^{nu}\). The residual vector is defined by \(\mathbf{r}\in\mathbb{R}^{nr}\) where nr describes its dimension in the Euclidean space. On the other hand, the activation function builds a cost value based on the definition of the residual vector. The residual vector has to be specialized in a derived classes.

The main computations are carring out in calc() and calcDiff() routines. calc() computes the cost (and its residual) and calcDiff() computes the derivatives of the cost function (and its residual). Concretely speaking, calcDiff() builds a linear-quadratic approximation of the cost function with the form: \(\mathbf{l_x}\in\mathbb{R}^{ndx}\), \(\mathbf{l_u}\in\mathbb{R}^{nu}\), \(\mathbf{l_{xx}}\in\mathbb{R}^{ndx\times ndx}\), \(\mathbf{l_{xu}}\in\mathbb{R}^{ndx\times nu}\), \(\mathbf{l_{uu}}\in\mathbb{R}^{nu\times nu}\) are the Jacobians and Hessians, respectively. Additionally, it is important to note that calcDiff() computes the derivatives using the latest stored values by calc(). Thus, we need to first run calc().

See also: ActivationModelAbstractTpl, ResidualModelAbstractTpl calc(), calcDiff(), createData()

Definition at line 64 of file cost-base.hpp.

Constructor & Destructor Documentation

◆ CostModelAbstractTpl() [1/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		std::shared_ptr< ActivationModelAbstract >	activation,
		std::shared_ptr< ResidualModelAbstract >	residual
	)

Initialize the cost model.

Parameters

[in]	state	State of the dynamical system
[in]	activation	Activation model
[in]	residual	Residual model

◆ CostModelAbstractTpl() [2/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		std::shared_ptr< ActivationModelAbstract >	activation,
		const std::size_t	nu
	)

Initialize the cost model.

Parameters

[in]	state	State of the dynamical system
[in]	activation	Activation model
[in]	nu	Dimension of control vector

◆ CostModelAbstractTpl() [3/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		std::shared_ptr< ActivationModelAbstract >	activation
	)

The default nu value is obtained from StateAbstractTpl::get_nv().

Parameters

[in]	state	State of the dynamical system
[in]	activation	Activation model

◆ CostModelAbstractTpl() [4/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		std::shared_ptr< ResidualModelAbstract >	residual
	)

We use ActivationModelQuadTpl as a default activation model (i.e., \(a=\frac{1}{2}\|\mathbf{r}\|^2\))

Parameters

[in]	state	State of the dynamical system
[in]	residual	Residual model

◆ CostModelAbstractTpl() [5/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		const std::size_t	nr,
		const std::size_t	nu
	)

We use ActivationModelQuadTpl as a default activation model (i.e., \(a=\frac{1}{2}\|\mathbf{r}\|^2\))

Parameters

[in]	state	State of the system
[in]	nr	Dimension of residual vector
[in]	nu	Dimension of control vector

◆ CostModelAbstractTpl() [6/6]

CostModelAbstractTpl	(	std::shared_ptr< StateAbstract >	state,
		const std::size_t	nr
	)

We use ActivationModelQuadTpl as a default activation model (i.e., \(a=\frac{1}{2}\|\mathbf{r}\|^2\)). Furthermore, the default nu value is obtained from StateAbstractTpl::get_nv().

Parameters

[in]	state	State of the dynamical system
[in]	nr	Dimension of residual vector
[in]	nu	Dimension of control vector

Member Function Documentation

◆ calc() [1/2]

virtual void calc	(	const std::shared_ptr< CostDataAbstract > &	data,
		const Eigen::Ref< const VectorXs > &	x,
		const Eigen::Ref< const VectorXs > &	u
	)

pure virtual

Compute the cost value and its residual vector.

Parameters

[in]	data	Cost data
[in]	x	State point \(\mathbf{x}\in\mathbb{R}^{ndx}\)
[in]	u	Control input \(\mathbf{u}\in\mathbb{R}^{nu}\)

Implemented in CostModelNumDiffTpl< _Scalar >, and CostModelResidualTpl< _Scalar >.

◆ calc() [2/2]

virtual void calc	(	const std::shared_ptr< CostDataAbstract > &	data,
		const Eigen::Ref< const VectorXs > &	x
	)

virtual

Compute the total cost value for nodes that depends only on the state.

It updates the total cost based on the state only. This function is used in the terminal nodes of an optimal control problem.

Parameters

[in]	data	Cost data
[in]	x	State point \(\mathbf{x}\in\mathbb{R}^{ndx}\)

Reimplemented in CostModelNumDiffTpl< _Scalar >, and CostModelResidualTpl< _Scalar >.

◆ calcDiff() [1/2]

virtual void calcDiff	(	const std::shared_ptr< CostDataAbstract > &	data,
		const Eigen::Ref< const VectorXs > &	x,
		const Eigen::Ref< const VectorXs > &	u
	)

pure virtual

Compute the Jacobian and Hessian of cost and its residual vector.

It computes the Jacobian and Hessian of the cost function. It assumes that calc() has been run first.

Parameters

[in]	data	Cost data
[in]	x	State point \(\mathbf{x}\in\mathbb{R}^{ndx}\)
[in]	u	Control input \(\mathbf{u}\in\mathbb{R}^{nu}\)

Implemented in CostModelNumDiffTpl< _Scalar >, and CostModelResidualTpl< _Scalar >.

◆ calcDiff() [2/2]

virtual void calcDiff	(	const std::shared_ptr< CostDataAbstract > &	data,
		const Eigen::Ref< const VectorXs > &	x
	)

virtual

Compute the Jacobian and Hessian of the cost functions with respect to the state only.

It updates the Jacobian and Hessian of the cost function based on the state only. This function is used in the terminal nodes of an optimal control problem.

Parameters

[in]	data	Cost data
[in]	x	State point \(\mathbf{x}\in\mathbb{R}^{ndx}\)

Reimplemented in CostModelNumDiffTpl< _Scalar >, and CostModelResidualTpl< _Scalar >.

◆ createData()

virtual std::shared_ptr<CostDataAbstract> createData ( DataCollectorAbstract *const data )

virtual

Create the cost data.

The default data contains objects to store the values of the cost, residual vector and their derivatives (first and second order derivatives). However, it is possible to specialize this function if we need to create additional data, for instance, to avoid dynamic memory allocation.

Parameters

data	Data collector

Returns: the cost data

Reimplemented in CostModelNumDiffTpl< _Scalar >, and CostModelResidualTpl< _Scalar >.

◆ print()

virtual void print ( std::ostream & os ) const

virtual

Print relevant information of the cost model.

Parameters

[out] os Output stream object

Reimplemented in CostModelResidualTpl< _Scalar >.

The documentation for this class was generated from the following file:

/root/robotpkg/optimization/py-crocoddyl/work/crocoddyl-2.1.0/include/crocoddyl/core/cost-base.hpp

Public Types

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Friends

Detailed Description

template<typename _Scalar> class crocoddyl::CostModelAbstractTpl< _Scalar >

Constructor & Destructor Documentation

◆ CostModelAbstractTpl() [1/6]

◆ CostModelAbstractTpl() [2/6]

◆ CostModelAbstractTpl() [3/6]

◆ CostModelAbstractTpl() [4/6]

◆ CostModelAbstractTpl() [5/6]

◆ CostModelAbstractTpl() [6/6]

Member Function Documentation

◆ calc() [1/2]

◆ calc() [2/2]

◆ calcDiff() [1/2]

◆ calcDiff() [2/2]

◆ createData()

◆ print()

template<typename _Scalar>
class crocoddyl::CostModelAbstractTpl< _Scalar >