Ruckig 0.15.1
Motion Generation for Robots and Machines
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Public Member Functions | Public Attributes | List of all members
ruckig::Trackig< DOFs, CustomVector > Class Template Reference

The main interface for the Trackig algorithm. More...

#include <trackig.hpp>

Public Member Functions

template<size_t D = DOFs, typename std::enable_if<(D >=1), int >::type = 0>
 Trackig (double delta_time)
 
template<size_t D = DOFs, typename std::enable_if<(D==0), int >::type = 0>
 Trackig (size_t dofs, double delta_time)
 
Result update (const TargetState< DOFs, CustomVector > &target_state, InputParameter< DOFs, CustomVector > &input, OutputParameter< DOFs, CustomVector > &output)
 Follow the given target state online.
 
std::vector< OutputParameter< DOFs, CustomVector > > calculate_trajectory (const std::vector< TargetState< DOFs, CustomVector > > &trajectory, InputParameter< DOFs, CustomVector > &input)
 Follow the fully-known trajectory in an offline manner.
 

Public Attributes

Calculator< DOFs, CustomVector > calculator
 Calculator for new trajectories.
 
const size_t degrees_of_freedom
 Degrees of freedom.
 
const double delta_time
 Time step between updates (cycle time)
 
TrackigMode mode
 Different modes of the trackig algorithm, e.g. for optimized or fast mode.
 
double reactiveness
 Weight for the reactiveness of the optimization, in [0.0, 1.0].
 
size_t look_ahead_cycles
 Number of cycles to look ahead at the initial solution of the optimization.
 
size_t max_iterations
 Maximum number of iterations for the optimization.
 
size_t last_iterations_counter
 Number of iterations used during the last optimization step.
 
std::function< TargetState< DOFs, CustomVector >(const TargetState< DOFs, CustomVector > &, double)> prediction_model
 The model for predicting the kinematic state into the future, the default is integration with constant acceleration.
 

Detailed Description

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
class ruckig::Trackig< DOFs, CustomVector >

The main interface for the Trackig algorithm.

Constructor & Destructor Documentation

◆ Trackig() [1/2]

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
template<size_t D = DOFs, typename std::enable_if<(D >=1), int >::type = 0>
ruckig::Trackig< DOFs, CustomVector >::Trackig ( double  delta_time)
inlineexplicit

◆ Trackig() [2/2]

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
template<size_t D = DOFs, typename std::enable_if<(D==0), int >::type = 0>
ruckig::Trackig< DOFs, CustomVector >::Trackig ( size_t  dofs,
double  delta_time 
)
inlineexplicit

Member Function Documentation

◆ calculate_trajectory()

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
std::vector< OutputParameter< DOFs, CustomVector > > ruckig::Trackig< DOFs, CustomVector >::calculate_trajectory ( const std::vector< TargetState< DOFs, CustomVector > > &  trajectory,
InputParameter< DOFs, CustomVector > &  input 
)
inline

Follow the fully-known trajectory in an offline manner.

◆ update()

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
Result ruckig::Trackig< DOFs, CustomVector >::update ( const TargetState< DOFs, CustomVector > &  target_state,
InputParameter< DOFs, CustomVector > &  input,
OutputParameter< DOFs, CustomVector > &  output 
)
inline

Follow the given target state online.

Member Data Documentation

◆ calculator

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
Calculator<DOFs, CustomVector> ruckig::Trackig< DOFs, CustomVector >::calculator

Calculator for new trajectories.

◆ degrees_of_freedom

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
const size_t ruckig::Trackig< DOFs, CustomVector >::degrees_of_freedom

Degrees of freedom.

◆ delta_time

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
const double ruckig::Trackig< DOFs, CustomVector >::delta_time

Time step between updates (cycle time)

◆ last_iterations_counter

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
size_t ruckig::Trackig< DOFs, CustomVector >::last_iterations_counter

Number of iterations used during the last optimization step.

◆ look_ahead_cycles

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
size_t ruckig::Trackig< DOFs, CustomVector >::look_ahead_cycles

Number of cycles to look ahead at the initial solution of the optimization.

◆ max_iterations

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
size_t ruckig::Trackig< DOFs, CustomVector >::max_iterations

Maximum number of iterations for the optimization.

◆ mode

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
TrackigMode ruckig::Trackig< DOFs, CustomVector >::mode

Different modes of the trackig algorithm, e.g. for optimized or fast mode.

◆ prediction_model

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
std::function<TargetState<DOFs, CustomVector>(const TargetState<DOFs, CustomVector>&, double)> ruckig::Trackig< DOFs, CustomVector >::prediction_model

The model for predicting the kinematic state into the future, the default is integration with constant acceleration.

◆ reactiveness

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>
double ruckig::Trackig< DOFs, CustomVector >::reactiveness

Weight for the reactiveness of the optimization, in [0.0, 1.0].


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