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)
void	reset ()
	Reset the instance (e.g. to force a new calculation in the next update)
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 resulting trajectory, 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 >(double, const TargetState< DOFs, CustomVector > &, bool &)>	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.

reset()

template<size_t DOFs, template< class, size_t > class CustomVector = StandardVector>

void ruckig::Trackig< DOFs, CustomVector >::reset ( )

inline

Reset the instance (e.g. to force a new calculation in the next update)

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.

In particular useful for reducing the worst case calculation time of the Optimized mode.

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>(double, const TargetState<DOFs, CustomVector>&, bool&)> 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 resulting trajectory, in [0.0, 1.0].

This time parameter scales the time parameter of (a) the target state prediction and (b) the generated trajectory of the follower. A lower parameter results in a more conservative target state prediction and a smoother overall motion. At zero, Trackig converges into regular trajectory generation as there is no target state prediction anymore.

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

• /home/runner/work/ruckig-pro/ruckig-pro/include/ruckig/trackig.hpp