Ruckig 0.15.0
Motion Generation for Robots and Machines
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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
 Parameter to tune the plan-ahead time of the controller, in [0.0, 1.0].
 
size_t look_ahead_cycles
 Parameter to tune how many cycle to look a head (for calculating trajectories)
 
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

Parameter to tune how many cycle to look a head (for calculating trajectories)

◆ 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

Parameter to tune the plan-ahead time of the controller, in [0.0, 1.0].


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