crocoddyl  1.8.1
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ActionModelAbstractTpl< _Scalar > Class Template Referenceabstract

Abstract class for action model. More...

#include <crocoddyl/core/action-base.hpp>

Inheritance diagram for ActionModelAbstractTpl< _Scalar >:

Public Types

typedef ActionDataAbstractTpl< Scalar > ActionDataAbstract
 
typedef MathBaseTpl< Scalar > MathBase
 
typedef StateAbstractTpl< Scalar > StateAbstract
 
typedef MathBase::VectorXs VectorXs
 

Public Member Functions

 ActionModelAbstractTpl (boost::shared_ptr< StateAbstract > state, const std::size_t nu, const std::size_t nr=0)
 Initialize the action model. More...
 
virtual void calc (const boost::shared_ptr< ActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0
 Compute the next state and cost value. More...
 
void calc (const boost::shared_ptr< ActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x)
 
virtual void calcDiff (const boost::shared_ptr< ActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0
 Compute the derivatives of the dynamics and cost functions. More...
 
void calcDiff (const boost::shared_ptr< ActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x)
 
virtual bool checkData (const boost::shared_ptr< ActionDataAbstract > &data)
 Checks that a specific data belongs to this model.
 
virtual boost::shared_ptr< ActionDataAbstractcreateData ()
 Create the action data. More...
 
bool get_has_control_limits () const
 Indicates if there are defined control limits.
 
std::size_t get_nr () const
 Return the dimension of the cost-residual vector.
 
std::size_t get_nu () const
 Return the dimension of the control input.
 
const boost::shared_ptr< StateAbstract > & get_state () const
 Return the state.
 
const VectorXs & get_u_lb () const
 Return the control lower bound.
 
const VectorXs & get_u_ub () const
 Return the control upper bound.
 
virtual void print (std::ostream &os) const
 Print relevant information of the action model. More...
 
virtual void quasiStatic (const boost::shared_ptr< ActionDataAbstract > &data, Eigen::Ref< VectorXs > u, const Eigen::Ref< const VectorXs > &x, const std::size_t maxiter=100, const Scalar tol=Scalar(1e-9))
 Computes the quasic static commands. More...
 
VectorXs quasiStatic_x (const boost::shared_ptr< ActionDataAbstract > &data, const VectorXs &x, const std::size_t maxiter=100, const Scalar tol=Scalar(1e-9))
 
void set_u_lb (const VectorXs &u_lb)
 Modify the control lower bounds.
 
void set_u_ub (const VectorXs &u_ub)
 Modify the control upper bounds.
 

Public Attributes

EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef _Scalar Scalar
 

Protected Member Functions

void update_has_control_limits ()
 Update the status of the control limits (i.e. if there are defined limits)
 

Protected Attributes

bool has_control_limits_
 Indicates whether any of the control limits is finite.
 
std::size_t nr_
 Dimension of the cost residual.
 
std::size_t nu_
 Control dimension.
 
boost::shared_ptr< StateAbstractstate_
 Model of the state.
 
VectorXs u_lb_
 Lower control limits.
 
VectorXs u_ub_
 Upper control limits.
 
VectorXs unone_
 Neutral state.
 

Friends

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

Detailed Description

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

Abstract class for action model.

In Crocoddyl, an action model combines dynamics and cost models. Each node, in our optimal control problem, is described through an action model. Every time that we want describe a problem, we need to provide ways of computing the dynamics, cost functions and their derivatives. All these is described inside the action model.

Concretely speaking, the action model describes a time-discrete action model with a first-order ODE along a cost function, i.e.

\[ \begin{aligned} &\delta\mathbf{x}^+ = \mathbf{f_{x}}\delta\mathbf{x}+\mathbf{f_{u}}\delta\mathbf{u}, &\textrm{(dynamics)}\\ &l(\delta\mathbf{x},\delta\mathbf{u}) = \begin{bmatrix}1 \\ \delta\mathbf{x} \\ \delta\mathbf{u}\end{bmatrix}^T \begin{bmatrix}0 & \mathbf{l_x}^T & \mathbf{l_u}^T \\ \mathbf{l_x} & \mathbf{l_{xx}} & \mathbf{l_{ux}}^T \\ \mathbf{l_u} & \mathbf{l_{ux}} & \mathbf{l_{uu}}\end{bmatrix} \begin{bmatrix}1 \\ \delta\mathbf{x} \\ \delta\mathbf{u}\end{bmatrix}, &\textrm{(cost)} \end{aligned} \]

where the state \(\mathbf{x}\in\mathcal{X}\) lies in the state manifold described with a nx-tuple, its rate \(\delta\mathbf{x}\in T_{\mathbf{x}}\mathcal{X}\) is a tangent vector to this manifold with ndx dimension, and \(\mathbf{u}\in\mathbb{R}^{nu}\) is the input commands. Note that the we could describe a linear or linearized action system, where the cost has a quadratic form.

The main computations are carrying out in calc and calcDiff. calc computes the next state and cost and calcDiff computes the derivatives of the dynamics and cost function. Concretely speaking, calcDiff builds a linear-quadratic approximation of an action model, where the dynamics and cost functions have linear and quadratic forms, respectively. \(\mathbf{f_x}\in\mathbb{R}^{nv\times ndx}\), \(\mathbf{f_u}\in\mathbb{R}^{nv\times nu}\) are the Jacobians of the dynamics; \(\mathbf{l_x}\in\mathbb{R}^{ndx}\), \(\mathbf{l_u}\in\mathbb{R}^{nu}\), \(\mathbf{l_{xx}}\in\mathbb{R}^{ndx\times ndx}\), \(\mathbf{l_{xu}}\in\mathbb{R}^{ndx\times nu}\), \(\mathbf{l_{uu}}\in\mathbb{R}^{nu\times nu}\) are the Jacobians and Hessians of the cost function, respectively. Additionally, it is important remark that calcDiff() computes the derivates using the latest stored values by calc(). Thus, we need to run first calc().

See also
calc(), calcDiff(), createData()

Definition at line 60 of file action-base.hpp.

Constructor & Destructor Documentation

◆ ActionModelAbstractTpl()

ActionModelAbstractTpl ( boost::shared_ptr< StateAbstract state,
const std::size_t  nu,
const std::size_t  nr = 0 
)

Initialize the action model.

Parameters
[in]stateState description
[in]nuDimension of control vector
[in]nrDimension of cost-residual vector

Member Function Documentation

◆ calc() [1/2]

virtual void calc ( const boost::shared_ptr< ActionDataAbstract > &  data,
const Eigen::Ref< const VectorXs > &  x,
const Eigen::Ref< const VectorXs > &  u 
)
pure virtual

Compute the next state and cost value.

Parameters
[in]dataAction data
[in]xState point
[in]uControl input

Implemented in ActionModelImpulseFwdDynamicsTpl< _Scalar >.

◆ calcDiff() [1/2]

virtual void calcDiff ( const boost::shared_ptr< ActionDataAbstract > &  data,
const Eigen::Ref< const VectorXs > &  x,
const Eigen::Ref< const VectorXs > &  u 
)
pure virtual

Compute the derivatives of the dynamics and cost functions.

It computes the partial derivatives of the dynamical system and the cost function. It assumes that calc() has been run first. This function builds a linear-quadratic approximation of the action model (i.e. dynamical system and cost function).

Parameters
[in]dataAction data
[in]xState point
[in]uControl input

Implemented in ActionModelImpulseFwdDynamicsTpl< _Scalar >.

◆ createData()

◆ calc() [2/2]

void calc ( const boost::shared_ptr< ActionDataAbstract > &  data,
const Eigen::Ref< const VectorXs > &  x 
)

Compute the next state and cost value.

Parameters
[in]dataAction data
[in]xState point

◆ calcDiff() [2/2]

void calcDiff ( const boost::shared_ptr< ActionDataAbstract > &  data,
const Eigen::Ref< const VectorXs > &  x 
)

Compute the derivatives of the dynamics and cost functions.

Parameters
[in]dataAction data
[in]xState point

◆ quasiStatic()

virtual void quasiStatic ( const boost::shared_ptr< ActionDataAbstract > &  data,
Eigen::Ref< VectorXs >  u,
const Eigen::Ref< const VectorXs > &  x,
const std::size_t  maxiter = 100,
const Scalar  tol = Scalar(1e-9) 
)
virtual

Computes the quasic static commands.

The quasic static commands are the ones produced for a the reference posture as an equilibrium point, i.e. for \(\mathbf{f^q_x}\delta\mathbf{q}+\mathbf{f_u}\delta\mathbf{u}=\mathbf{0}\)

Parameters
[in]dataAction data
[out]uQuasic static commands
[in]xState point (velocity has to be zero)
[in]maxiterMaximum allowed number of iterations
[in]tolTolerance

◆ quasiStatic_x()

VectorXs quasiStatic_x ( const boost::shared_ptr< ActionDataAbstract > &  data,
const VectorXs &  x,
const std::size_t  maxiter = 100,
const Scalar  tol = Scalar(1e-9) 
)
Parameters
[in]dataAction data
[in]xState point (velocity has to be zero)
[in]maxiterMaximum allowed number of iterations
[in]tolTolerance
Returns
Quasic static commands

◆ print()

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

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