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roboptim::trajectory::StablePointStateFunction< T > Class Template Reference
Mathematical abstract functions

Trajectory cost function defined by state evaluation at parameter. More...

#include <roboptim/trajectory/stable-point-state-function.hh>

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Public Types

typedef T trajectory_t
 Trajectory type.

Public Member Functions

 StablePointStateFunction (const trajectory_t &gamma, boost::shared_ptr< DerivableFunction > cost, const StableTimePoint tpt, size_type order=1)
 Constructor.
virtual ~StablePointStateFunction ()
size_type order () const

Static Public Member Functions

template<typename F, typename CLIST>
static void addToProblem (const trajectory_t &trajectory, boost::shared_ptr< DerivableFunction > function, unsigned order, Problem< F, CLIST > &problem, typename Function::interval_t bounds, unsigned nConstraints)

Protected Member Functions

void impl_compute (result_ref, const_argument_ref) const
void impl_gradient (gradient_ref, const_argument_ref, size_type) const

Detailed Description

template<typename T>
class roboptim::trajectory::StablePointStateFunction< T >

Trajectory cost function defined by state evaluation at parameter.

The state along a trajectory is defined as the vector containing the configuration and derivatives up to order $r$ of the configuration.

\‍[\textbf{Cost}(\Gamma) = cost \left({\Gamma(t)}, {\dot{\Gamma}(t)},\cdots,\frac{d^{r}\Gamma}{dt^{r}}(t) \right) \‍]

where

  • $\textbf{Cost}$ is the trajectory cost,
  • $cost$ is the state cost,
  • $t$ is the parameter along the trajectory where the cost is evaluated (fixed at construction),
  • $r$ is called the order of the state.
Template Parameters
Ttrajectory type

Member Typedef Documentation

◆ trajectory_t

template<typename T>
typedef T roboptim::trajectory::StablePointStateFunction< T >::trajectory_t

Trajectory type.

Constructor & Destructor Documentation

◆ StablePointStateFunction()

template<typename T>
roboptim::trajectory::StablePointStateFunction< T >::StablePointStateFunction ( const trajectory_t & gamma,
boost::shared_ptr< DerivableFunction > cost,
const StableTimePoint tpt,
size_type order = 1 )

Constructor.

Parameters
gammaTrajectory $\Gamma$ along which the state is evaluated.
coststate cost: $cost$.
tptparameter $t$ where the state is evaluated.
orderorder $r$ of derivation.

References order().

Referenced by addToProblem().

◆ ~StablePointStateFunction()

template<typename T>
roboptim::trajectory::StablePointStateFunction< T >::~StablePointStateFunction ( )
virtual

Member Function Documentation

◆ addToProblem()

template<typename T>
template<typename F, typename CLIST>
void roboptim::trajectory::StablePointStateFunction< T >::addToProblem ( const trajectory_t & trajectory,
boost::shared_ptr< DerivableFunction > function,
unsigned order,
Problem< F, CLIST > & problem,
typename Function::interval_t bounds,
unsigned nConstraints )
inlinestatic

References order(), StablePointStateFunction(), and roboptim::trajectory::tMax.

◆ impl_compute()

template<typename T>
void roboptim::trajectory::StablePointStateFunction< T >::impl_compute ( result_ref res,
const_argument_ref p ) const
protected

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

◆ impl_gradient()

template<typename T>
void roboptim::trajectory::StablePointStateFunction< T >::impl_gradient ( gradient_ref grad,
const_argument_ref p,
size_type i ) const
protected

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

◆ order()

template<typename T>
StablePointStateFunction< T >::size_type roboptim::trajectory::StablePointStateFunction< T >::order ( ) const

Referenced by addToProblem(), and StablePointStateFunction().