Trajectory cost function defined by state evaluation at parameter. More...
#include <roboptim/trajectory/state-function.hh>
  
 Public Types | |
| typedef T | trajectory_t | 
| Trajectory type.   | |
Public Member Functions | |
| StateFunction (const trajectory_t &gamma, boost::shared_ptr< DerivableFunction > cost, const StableTimePoint tpt, size_type order=1) | |
| Constructor.   | |
| virtual | ~StateFunction () | 
| size_type | order () const | 
Static Public Member Functions | |
| template<typename M > | |
| static void | addToProblem (const trajectory_t &trajectory, boost::shared_ptr< DerivableFunction > function, unsigned order, Problem< M > &problem, typename Function::interval_t bounds, unsigned nConstraints) | 
| template<typename M > | |
| static void | addToProblem (const trajectory_t &trajectory, boost::shared_ptr< DerivableFunction > function, unsigned order, Problem< M > &problem, const typename Function::intervals_t &bounds, const std::vector< typename Function::value_type > &scales, 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 | 
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
| T | trajectory type | 
| typedef T roboptim::trajectory::StateFunction< T >::trajectory_t | 
Trajectory type.
| roboptim::trajectory::StateFunction< T >::StateFunction | ( | const trajectory_t & | gamma, | 
| boost::shared_ptr< DerivableFunction > | cost, | ||
| const StableTimePoint | tpt, | ||
| size_type | order = 1  | 
        ||
| ) | 
Constructor.
| gamma | Trajectory \(\Gamma\) along which the state is evaluated. | 
| cost | state cost: \(cost\). | 
| tpt | parameter \(t\) where the state is evaluated. | 
| order | order \(r\) of derivation. | 
| std::runtime_error | 
| roboptim::trajectory::StateFunction< T >::~StateFunction | ( | ) |  [virtual] | 
        
| static void roboptim::trajectory::StateFunction< T >::addToProblem | ( | const trajectory_t & | trajectory, | 
| boost::shared_ptr< DerivableFunction > | function, | ||
| unsigned | order, | ||
| Problem< M > & | problem, | ||
| typename Function::interval_t | bounds, | ||
| unsigned | nConstraints | ||
| ) |  [inline, static] | 
        
| M | Eigen matrix type | 
References roboptim::trajectory::tMax.
| static void roboptim::trajectory::StateFunction< T >::addToProblem | ( | const trajectory_t & | trajectory, | 
| boost::shared_ptr< DerivableFunction > | function, | ||
| unsigned | order, | ||
| Problem< M > & | problem, | ||
| const typename Function::intervals_t & | bounds, | ||
| const std::vector< typename Function::value_type > & | scales, | ||
| unsigned | nConstraints | ||
| ) |  [inline, static] | 
        
References roboptim::trajectory::tMax.
| void roboptim::trajectory::StateFunction< T >::impl_compute | ( | result_ref | res, | 
| const_argument_ref | p | ||
| ) |  const [protected] | 
        
ROBOPTIM_DO_NOT_CHECK_ALLOCATION
ROBOPTIM_DO_NOT_CHECK_ALLOCATION
| void roboptim::trajectory::StateFunction< 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
| StateFunction< T >::size_type roboptim::trajectory::StateFunction< T >::order | ( | ) | const |