Implementation of Contextual Dynamical Movement Primitives. More...

#include <DmpContextual.hpp>

Inheritance diagram for DmpContextual:

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Collaboration diagram for DmpContextual:

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Public Member Functions
	DmpContextual (int n_dims_dmp, std::vector< FunctionApproximator * > function_approximators, DmpType dmp_type)
	Initialization constructor for Contextual DMPs of known dimensionality, but with unknown initial and attractor states. More...

void	set_task_parameters (const Eigen::MatrixXd &task_parameters)
	Set the current task parameters. More...

void	set_policy_parameter_function_goal (FunctionApproximator *function_approximator)
	Set a function approximator to predict the goal from the task parameters. More...

void	set_policy_parameter_function_duration (FunctionApproximator *function_approximator)
	Set a function approximator to predict the duration from the task parameters. More...

virtual void	computeFunctionApproximatorOutput (const Eigen::Ref< const Eigen::MatrixXd > &phase_state, Eigen::MatrixXd &fa_output) const =0
	Compute the outputs of the function approximators. More...

virtual void	train (const std::vector< Trajectory > &trajectories, const std::vector< Eigen::MatrixXd > &task_parameters, std::string save_directory, bool overwrite)=0
	Train a contextual Dmp with a set of trajectories (and save results to file) This function is useful for debugging, i.e. More...

void	train (const std::vector< Trajectory > &trajectories, const std::vector< Eigen::MatrixXd > &task_parameters, std::string save_directory)
	Train a contextual DMP with multiple trajectories. More...

void	train (const std::vector< Trajectory > &trajectories, const std::vector< Eigen::MatrixXd > &task_parameters)
	Train a contextual DMP with multiple trajectories. More...

void	train (const std::vector< Trajectory > &trajectories, std::string save_directory, bool overwrite)
	Train a contextual DMP with multiple trajectories. More...

void	train (const std::vector< Trajectory > &trajectories, std::string save_directory)
	Train a contextual DMP with multiple trajectories. More...

void	train (const std::vector< Trajectory > &trajectories)
	Train a contextual DMP with multiple trajectories. More...

Public Member Functions inherited from Dmp
	Dmp (double tau, Eigen::VectorXd y_init, Eigen::VectorXd y_attr, std::vector< FunctionApproximator * > function_approximators, double alpha_spring_damper, DynamicalSystem goal_system, DynamicalSystem phase_system, DynamicalSystem *gating_system, ForcingTermScaling scaling=NO_SCALING)
	Initialization constructor. More...

	Dmp (int n_dims_dmp, std::vector< FunctionApproximator * > function_approximators, double alpha_spring_damper, DynamicalSystem goal_system, DynamicalSystem phase_system, DynamicalSystem *gating_system, ForcingTermScaling scaling=NO_SCALING)
	Initialization constructor for Dmps of known dimensionality, but with unknown initial and attractor states. More...

	Dmp (double tau, Eigen::VectorXd y_init, Eigen::VectorXd y_attr, std::vector< FunctionApproximator * > function_approximators, DmpType dmp_type=KULVICIUS_2012_JOINING, ForcingTermScaling scaling=NO_SCALING)
	Constructor that initializes the DMP with default dynamical systems. More...

	Dmp (int n_dims_dmp, std::vector< FunctionApproximator * > function_approximators, DmpType dmp_type=KULVICIUS_2012_JOINING, ForcingTermScaling scaling=NO_SCALING)
	Initialization constructor for Dmps of known dimensionality, but with unknown initial and attractor states. More...

	Dmp (double tau, Eigen::VectorXd y_init, Eigen::VectorXd y_attr, double alpha_spring_damper, DynamicalSystem *goal_system)
	Initialization constructor for Dmps without a forcing term. More...

	~Dmp (void)
	Destructor. More...

Dmp *	clone (void) const
	Return a deep copy of this object. More...

virtual void	integrateStart (Eigen::Ref< Eigen::VectorXd > x, Eigen::Ref< Eigen::VectorXd > xd) const
	Start integrating the system. More...

void	differentialEquation (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::Ref< Eigen::VectorXd > xd) const
	The differential equation which defines the system. More...

void	analyticalSolution (const Eigen::VectorXd &ts, Eigen::MatrixXd &xs, Eigen::MatrixXd &xds, Eigen::MatrixXd &forcing_terms, Eigen::MatrixXd &fa_output) const
	Return analytical solution of the system at certain times (and return forcing terms) More...

void	analyticalSolution (const Eigen::VectorXd &ts, Eigen::MatrixXd &xs, Eigen::MatrixXd &xds, Eigen::MatrixXd &forcing_terms) const
	Return analytical solution of the system at certain times (and return forcing terms) More...

void	analyticalSolution (const Eigen::VectorXd &ts, Eigen::MatrixXd &xs, Eigen::MatrixXd &xds) const
	Return analytical solution of the system at certain times. More...

virtual void	analyticalSolution (const Eigen::VectorXd &ts, Trajectory &trajectory) const
	Return analytical solution of the system at certain times. More...

void	analyticalSolution (const Eigen::VectorXd &ts, Trajectory &trajectory, Eigen::MatrixXd &forcing_terms) const
	Return analytical solution of the system at certain times. More...

virtual void	statesAsTrajectory (const Eigen::MatrixXd &x_in, const Eigen::MatrixXd &xd_in, Eigen::MatrixXd &y_out, Eigen::MatrixXd &yd_out, Eigen::MatrixXd &ydd_out) const
	Get the output of a DMP dynamical system as a trajectory. More...

virtual void	statesAsTrajectory (const Eigen::VectorXd &ts, const Eigen::MatrixXd &x_in, const Eigen::MatrixXd &xd_in, Trajectory &trajectory) const
	Get the output of a DMP dynamical system as a trajectory. More...

virtual void	train (const Trajectory &trajectory)
	Train a DMP with a trajectory. More...

virtual void	train (const Trajectory &trajectory, std::string save_directory, bool overwrite=false)
	Train a DMP with a trajectory, and write results to file. More...

virtual void	set_tau (double tau)
	Accessor function for the time constant. More...

virtual void	set_initial_state (const Eigen::VectorXd &y_init)
	Accessor function for the initial state of the system. More...

virtual void	set_attractor_state (const Eigen::VectorXd &y_attr)
	Accessor function for the attractor state of the system. More...

void	set_damping_coefficient (double damping_coefficient)
	Accessor function for damping coefficient of spring-damper system. More...

void	set_spring_constant (double spring_constant)
	Accessor function for spring constant of spring-damper system. More...

std::string	toString (void) const
	Returns a string representation of the object. More...

void	getSelectableParameters (std::set< std::string > &selectable_values_labels) const
	Return all the names of the parameter types that can be selected. More...

void	setSelectedParameters (const std::set< std::string > &selected_values_labels)
	Determine which subset of parameters is represented in the vector returned by Parameterizable::getParameterVectorSelected. More...

int	getParameterVectorAllSize (void) const
	Get the size of the parameter values vector when it contains all available parameter values. More...

void	getParameterVectorAll (Eigen::VectorXd &values) const
	Return a vector that returns all available parameter values. More...

void	setParameterVectorAll (const Eigen::VectorXd &values)
	Set all available parameter values with one vector. More...

void	getParameterVectorMask (const std::set< std::string > selected_values_labels, Eigen::VectorXi &selected_mask) const
	Get a mask for selecting parameters. More...

void	computeFunctionApproximatorInputsAndTargets (const Trajectory &trajectory, Eigen::VectorXd &fa_inputs_phase, Eigen::MatrixXd &fa_targets) const
	Given a trajectory, compute the inputs and targets for the function approximators. More...

void	set_perturbation_analytical_solution (double perturbation_standard_deviation)
	Add a perturbation to the forcing term when computing the analytical solution. More...

double	get_perturbation_analytical_solution () const
	Get the perturbation to the forcing term when computing the analytical solution. More...

Public Member Functions inherited from DynamicalSystem
	DynamicalSystem (int order, double tau, Eigen::VectorXd initial_state, Eigen::VectorXd attractor_state, std::string name)
	Initialization constructor. More...

virtual	~DynamicalSystem (void)
	Destructor.

void	integrateStart (const Eigen::VectorXd &x_init, Eigen::Ref< Eigen::VectorXd > x, Eigen::Ref< Eigen::VectorXd > xd)
	Start integrating the system with a new initial state. More...

virtual void	integrateStep (double dt, const Eigen::Ref< const Eigen::VectorXd > x, Eigen::Ref< Eigen::VectorXd > x_updated, Eigen::Ref< Eigen::VectorXd > xd_updated) const
	Integrate the system one time step. More...

void	set_integration_method (IntegrationMethod integration_method)
	Choose the integration method. More...

int	dim (void) const
	Get the dimensionality of the dynamical system, i.e. More...

int	dim_orig (void) const
	Get the dimensionality of the dynamical system, i.e. More...

double	tau (void) const
	Accessor function for the time constant. More...

Eigen::VectorXd	initial_state (void) const
	Accessor function for the initial state of the dynamical system. More...

void	initial_state (Eigen::VectorXd &initial_state) const
	Accessor function for the initial state of the dynamical system. More...

Eigen::VectorXd	attractor_state (void) const
	Accessor function for the attractor state of the dynamical system. More...

void	attractor_state (Eigen::VectorXd &attractor_state) const
	Accessor function for the attractor state of the dynamical system. More...

virtual void	set_attractor_state (const Eigen::Ref< const Eigen::VectorXd > &attractor_state)
	Mutator function for the attractor state of the dynamical system. More...

std::string	name (void) const
	Accessor function for the name of the dynamical system. More...

virtual void	set_name (std::string name)
	Mutator function for the name of the dynamical system. More...

Public Member Functions inherited from Parameterizable
virtual	~Parameterizable (void)
	Destructor.

virtual int	getParameterVectorSelectedSize (void) const
	Get the size of the vector of selected parameters, as returned by getParameterVectorSelected(. More...

virtual void	getParameterVectorSelected (Eigen::VectorXd &values, bool normalized=false) const
	Get the values of the selected parameters in one vector. More...

virtual void	getParameterVectorSelectedNormalized (Eigen::VectorXd &values) const
	Get the normalized values of the selected parameters in one vector. More...

void	getParameterVectorSelectedMinMax (Eigen::VectorXd &min, Eigen::VectorXd &max) const
	Get the minimum and maximum of the selected parameters in one vector. More...

void	getParameterVectorAllMinMax (Eigen::VectorXd &min, Eigen::VectorXd &max) const
	Get the minimum and maximum values of the current parameter vector. More...

void	getParameterVectorSelectedRanges (Eigen::VectorXd &ranges) const
	Get the ranges of the selected parameters, i.e. More...

virtual void	setParameterVectorSelected (const Eigen::VectorXd &values, bool normalized=false)
	Set all the values of the selected parameters with one vector. More...

virtual void	setParameterVectorSelectedNormalized (const Eigen::VectorXd &values)
	Set all the values of the selected parameters with one vector of normalized values. More...

void	setSelectedParametersOne (std::string selected)
	Set the parameters that are currently selected. More...

void	setParameterVectorModifier (std::string modifier, bool new_value)
	Turn certain modifiers on or off. More...

void	setVectorLengthsPerDimension (const Eigen::VectorXi &lengths_per_dimension)
	The vector (VectorXd) with parameter values can be split into different parts (as vector<VectorXd>; this function specifices the length of each sub-vector. More...

Eigen::VectorXi	getVectorLengthsPerDimension (void) const
	Get the specified length of each vector in each dimension. More...

void	getParameterVectorSelected (std::vector< Eigen::VectorXd > &values, bool normalized=false) const
	Get the values of the selected parameters in one vector. More...

void	setParameterVectorSelected (const std::vector< Eigen::VectorXd > &values, bool normalized=false)
	Set all the values of the selected parameters with a vector of vectors. More...

Protected Member Functions
void	trainLocal (const std::vector< Trajectory > &trajectories, const std::vector< Eigen::MatrixXd > &task_parameters, std::string save_directory, bool overwrite)
	Train a contextual DMP. More...

void	checkTrainTrajectories (const std::vector< Trajectory > &trajectories)
	Check if several trajectories have the same duration and initial/final states. More...

Protected Member Functions inherited from Dmp
FunctionApproximator *	function_approximator (int i_dim) const
	Get a pointer to the function approximator for a certain dimension. More...

Protected Member Functions inherited from DynamicalSystem
	DynamicalSystem (void)
	Default constructor. More...

void	set_dim (int dim)
	Set the dimensionality of the dynamical system, i.e. More...

Protected Attributes
Eigen::MatrixXd	task_parameters_
	The current task parameters.

std::vector< FunctionApproximator * >	policy_parameter_function_goal_
	FunctionApproximators that relate task parameters the goal of the DMP.

FunctionApproximator *	policy_parameter_function_duration_
	FunctionApproximator that relates task parameters the duration of the DMP.

Friends
class	boost::serialization::access
	Give boost serialization access to private members. More...

Additional Inherited Members
Public Types inherited from Dmp
enum	DmpType { IJSPEERT_2002_MOVEMENT, KULVICIUS_2012_JOINING, COUNTDOWN_2013 }
	Different types of DMPs that can be initialized. More...

enum	ForcingTermScaling { NO_SCALING, G_MINUS_Y0_SCALING, AMPLITUDE_SCALING }
	Different ways to scale the forcing term. More...

Public Types inherited from DynamicalSystem
enum	IntegrationMethod { EULER, RUNGE_KUTTA }
	The possible integration methods that can be used. More...

Detailed Description

Implementation of Contextual Dynamical Movement Primitives.

Contextual Dmp extends a 'standard' Dmp by adapting to task parameters.

See [12], [7], [2], [6]

This is how a 'standard' Dmp would be integrated

VectorXd x, xd, x_updated;
dmp->integrateStart(x,xd);
for (int t=1; t<T; t++) {
  dmp->integrateStep(dt,x,x_updated,xd); 
  x = x_updated;
}

A contextual Dmp is integrated as follows.

VectorXd x, xd, x_updated;
dmp->set_task_parameters(some_task_parameters);
dmp->integrateStart(x,xd);
for (int t=1; t<T; t++) {
  dmp->integrateStep(dt,x,x_updated,xd); 
  x = x_updated;
}

Or, if the task parameters change over time.

VectorXd x, xd, x_updated;
dmp->integrateStart(x,xd);
for (int t=1; t<T; t++) {
  dmp->set_task_parameters(some_task_parameters);
  dmp->integrateStep(dt,x,x_updated,xd); 
  x = x_updated;
}

Definition at line 79 of file DmpContextual.hpp.

Constructor & Destructor Documentation

DmpContextual	(	int	n_dims_dmp,
		std::vector< FunctionApproximator * >	function_approximators,
		DmpType	dmp_type
	)

Initialization constructor for Contextual DMPs of known dimensionality, but with unknown initial and attractor states.

Initializes the DMP with default dynamical systems.

Parameters

n_dims_dmp	Dimensionality of the DMP
function_approximators	Function approximators for the forcing term
dmp_type	The type of DMP, see Dmp::DmpType

Definition at line 39 of file DmpContextual.cpp.

 :  Dmp(n_dims_dmp, function_approximators, dmp_type)
 {
   policy_parameter_function_goal_ = std::vector<FunctionApproximator*>(0);
   policy_parameter_function_duration_ = NULL;
 }

Member Function Documentation

void set_task_parameters ( const Eigen::MatrixXd & task_parameters )

Set the current task parameters.

Parameters

[in] task_parameters Current task parameters

Definition at line 140 of file DmpContextual.cpp.

 {
   assert(task_parameters_.cols()==task_parameters.cols());
   task_parameters_ = task_parameters; // This will be used for the forcing term later
   
   // Compute new attractor state now, if necessary.
   if (policy_parameter_function_goal_.size()>0)
   { 
     // TODO: Check size of task_parameters
     VectorXd goal(dim_orig());
     MatrixXd outputs;
     for (int i_dim=0; i_dim<dim_orig(); i_dim++)
     {
       policy_parameter_function_goal_[i_dim]->predict(task_parameters,outputs);
       goal(i_dim) = outputs(0,0);
     }
     set_attractor_state(goal);
   }
   
   // Compute new duration now, if necessary.
   if (policy_parameter_function_duration_!=NULL)
   {
     // TODO: Check size of task_parameters
     MatrixXd duration_as_matrix;
     policy_parameter_function_duration_->predict(task_parameters,duration_as_matrix);
     set_tau(duration_as_matrix(0,0));
   }
   
 }

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void set_policy_parameter_function_goal ( FunctionApproximator * function_approximator )

Set a function approximator to predict the goal from the task parameters.

Parameters

[in] function_approximator The function approximator.

Definition at line 46 of file DmpContextual.cpp.

 {
   // Make clones, one for each of the dimensions of the goal
   policy_parameter_function_goal_ = vector<FunctionApproximator*>(dim_orig());
   for (int dd=0; dd<dim_orig(); dd++)
   { 
     policy_parameter_function_goal_[dd] = function_approximator->clone();
   }
 }

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void set_policy_parameter_function_duration ( FunctionApproximator * function_approximator )

Set a function approximator to predict the duration from the task parameters.

Parameters

[in] function_approximator The function approximator.

Definition at line 56 of file DmpContextual.cpp.

 {
   // Output of this function approximator should always be 1D (duration is time is 1D)
   assert(function_approximator->getExpectedOutputDim()==1);
 
   policy_parameter_function_duration_ = function_approximator->clone();  
 }

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virtual void computeFunctionApproximatorOutput	(	const Eigen::Ref< const Eigen::MatrixXd > &	phase_state,
		Eigen::MatrixXd &	fa_output
	)		const

pure virtual

Compute the outputs of the function approximators.

Parameters

[in]	phase_state	The phase states for which the outputs are computed.
[out]	fa_output	The outputs of the function approximators.

Reimplemented from Dmp.

Implemented in DmpContextualTwoStep, and DmpContextualOneStep.

void trainLocal	(	const std::vector< Trajectory > &	trajectories,
		const std::vector< Eigen::MatrixXd > &	task_parameters,
		std::string	save_directory,
		bool	overwrite
	)

protected

Train a contextual DMP.

All other train functions in this class directly or indirectly call this function. This function trains the function approximators for the policy parameter function for the goal and tau parameters. It then calls the train function in the subclasses (e.g. DmpContextualOneStep::train() or DmpContextualTwoStep::train() to train the forcing term.

Parameters

[in]	trajectories	The set of trajectories
[in]	task_parameters	The task parameters for each of the trajectories.
[in]	save_directory	Directory to which to save intermediate results.
[in]	overwrite	Overwrite existing files in the directory above

Definition at line 82 of file DmpContextual.cpp.

 {
   if (policy_parameter_function_goal_.size()>0 || policy_parameter_function_duration_!=NULL)
   {
     unsigned int n_demonstrations = trajectories.size();
     assert(n_demonstrations==task_parameters.size());  
     
     // Gather task parameters in a matrix
     int n_task_parameters = task_parameters[0].cols();
     MatrixXd inputs(n_demonstrations,n_task_parameters);
     for (unsigned int i_demo=0; i_demo<n_demonstrations; i_demo++)
       // Take the first row, i.e. at time_i = 0. 
       inputs.row(i_demo) = task_parameters[i_demo].row(0);
 
     if (policy_parameter_function_goal_.size()>0)
     {
       // Gather goals (target values for approximation) in one matrix
       MatrixXd targets(n_demonstrations,dim_orig());
       for (unsigned int i_demo=0; i_demo<n_demonstrations; i_demo++)
         targets.row(i_demo) = trajectories[i_demo].final_y();
       
       //cout << "  inputs=" << inputs << endl;
       //cout << "  targets=" << targets << endl;
       //cout << "  targets.col(0)=" << targets.col(0) << endl;
       
       for (int i_dim=0; i_dim<dim_orig(); i_dim++)
       {
         string save_directory_cur;
         if (!save_directory.empty())
             save_directory_cur = save_directory + "/dim" + to_string(i_dim) + "_goal";
         
         policy_parameter_function_goal_[i_dim]->train(inputs,targets.col(i_dim),save_directory_cur,overwrite);
       }
     }
     
     if (policy_parameter_function_duration_!=NULL)
     {
       // Gather durations (target values for approximation) in one matrix
       VectorXd targets(n_demonstrations);
       for (unsigned int i_demo=0; i_demo<n_demonstrations; i_demo++)
         targets(i_demo) = trajectories[i_demo].duration();
       
       //cout << "  inputs=" << inputs << endl;
       //cout << "  targets=" << targets << endl;
       
       string save_directory_cur;
       if (!save_directory.empty())
           save_directory_cur = save_directory + "/_duration";
       
       policy_parameter_function_duration_->train(inputs,targets,save_directory_cur,overwrite);
     }
     
   }
   
   // Train the rest, i.e. the parameters for the forcing term.
   train(trajectories, task_parameters, save_directory, overwrite);
 }

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virtual void train	(	const std::vector< Trajectory > &	trajectories,
		const std::vector< Eigen::MatrixXd > &	task_parameters,
		std::string	save_directory,
		bool	overwrite
	)

pure virtual

Train a contextual Dmp with a set of trajectories (and save results to file) This function is useful for debugging, i.e.

if you want to save intermediate results to a directory

Parameters

[in]	trajectories	The set of trajectories
[in]	task_parameters	The task parameters for each of the trajectories.
[in]	save_directory	Directory to which to save intermediate results.
[in]	overwrite	Overwrite existing files in the directory above Overloads Dmp::train

Implemented in DmpContextualTwoStep, and DmpContextualOneStep.

void train	(	const std::vector< Trajectory > &	trajectories,
		const std::vector< Eigen::MatrixXd > &	task_parameters,
		std::string	save_directory
	)

Train a contextual DMP with multiple trajectories.

Parameters

[in]	trajectories	A set of demonstrated trajectories
[in]	task_parameters	The task_parameters for each trajectory. It is a std::vector, where each task parameter element corresponds to one Trajectory. Each element is a matrix of size n_time_steps x n_task_paramaters
[in]	save_directory	Directory to which to save intermediate results. Does not overwrite existing files.

Definition at line 68 of file DmpContextual.cpp.

 {
   bool overwrite = false;
   train(trajectories, task_parameters, save_directory, overwrite);
 }

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void train	(	const std::vector< Trajectory > &	trajectories,
		const std::vector< Eigen::MatrixXd > &	task_parameters
	)

Train a contextual DMP with multiple trajectories.

Parameters

[in]	trajectories	A set of demonstrated trajectories
[in]	task_parameters	The task_parameters for each trajectory. It is a std::vector, where each task parameter element corresponds to one Trajectory. Each element is a matrix of size n_time_steps x n_task_paramaters

Definition at line 74 of file DmpContextual.cpp.

 {
   bool overwrite=false;
   string save_directory("");
   train(trajectories, task_parameters, save_directory, overwrite);
 }

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void train	(	const std::vector< Trajectory > &	trajectories,
		std::string	save_directory,
		bool	overwrite
	)

Train a contextual DMP with multiple trajectories.

Parameters

[in]	trajectories	A set of demonstrated trajectories, the task parameters are stored as miscellaneous variables in the trajectory, see also Trajectory::misc()
[in]	save_directory	Directory to which to save intermediate results
[in]	overwrite	Overwrite existing files in the directory above

Definition at line 170 of file DmpContextual.cpp.

 {
   vector<MatrixXd> task_parameters(trajectories.size());
   for (unsigned int i_traj=0; i_traj<trajectories.size(); i_traj++)
   {
     task_parameters[i_traj] = trajectories[i_traj].misc();
     assert(task_parameters[i_traj].cols()>0);
     if (i_traj>0)
       assert(task_parameters[i_traj].cols() ==  task_parameters[i_traj].cols());
   }
   trainLocal(trajectories, task_parameters, save_directory, overwrite);
 }

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void train	(	const std::vector< Trajectory > &	trajectories,
		std::string	save_directory
	)

Train a contextual DMP with multiple trajectories.

Parameters

[in]	trajectories	A set of demonstrated trajectories, the task parameters are stored as miscellaneous variables in the trajectory, see also Trajectory::misc()
[in]	save_directory	Directory to which to save intermediate results. Does not overwrite existing files.

Definition at line 183 of file DmpContextual.cpp.

 {
   bool overwrite=false;
   train(trajectories, save_directory, overwrite);
 }

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void train ( const std::vector< Trajectory > & trajectories )

Train a contextual DMP with multiple trajectories.

Parameters

[in] trajectories A set of demonstrated trajectories, the task parameters are stored as miscellaneous variables in the trajectory, see also Trajectory::misc()

Definition at line 189 of file DmpContextual.cpp.

 {
   bool overwrite=false;
   string save_directory("");
   train(trajectories, save_directory, overwrite);
 }

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void checkTrainTrajectories ( const std::vector< Trajectory > & trajectories )

protected

Check if several trajectories have the same duration and initial/final states.

Parameters

[in] trajectories A set of trajectories

Definition at line 197 of file DmpContextual.cpp.

 {
   // Check if inputs are of the right size.
   unsigned int n_demonstrations = trajectories.size();
   
   // Then check if the trajectories have the same duration and initial/final state
   double first_duration = trajectories[0].duration();
   VectorXd first_y_init = trajectories[0].initial_y();
   VectorXd first_y_attr = trajectories[0].final_y();  
   for (unsigned int i_demo=1; i_demo<n_demonstrations; i_demo++)
   {
     // Difference in tau
     if (fabs(first_duration-trajectories[i_demo].duration())>10e-4)
       {
         if (policy_parameter_function_duration_==NULL) 
         {
           cerr << __FILE__ << ":" << __LINE__ << ":";
           cerr << "WARNING: Duration of demonstrations differ (" << first_duration << "!=" << trajectories[i_demo].duration() << ")" << endl;
           cerr << "         See DmpContextual::set_policy_parameter_function_duration(...) on how to fix this. " << endl;
         }
       }
     
     // Difference between initial states
     double sum_abs_diff = (first_y_init.array()-trajectories[i_demo].initial_y().array()).abs().sum();
     if (sum_abs_diff>10e-7)
     {
       cerr << __FILE__ << ":" << __LINE__ << ":";
       cerr << "WARNING: Initial states of demonstrations differ ( [" << first_y_init.transpose() << "] != [ " << trajectories[i_demo].initial_y().transpose() << "] )" << endl;
     }
     
     // Difference between final states
     sum_abs_diff = (first_y_attr.array()-trajectories[i_demo].final_y().array()).abs().sum();
     if (sum_abs_diff>10e-7 && policy_parameter_function_goal_.size()==0)
     {
       cerr << __FILE__ << ":" << __LINE__ << ":";
       cerr << "WARNING: Final states of demonstrations differ ( [" << first_y_attr.transpose() << "] != [ " << trajectories[i_demo].final_y().transpose() << "] )" << endl;
       cerr << "         See DmpContextual::set_policy_parameter_function_goal(...) on how to fix this. " << endl;
     }
     
   }
 }

Friends And Related Function Documentation

friend class boost::serialization::access

friend

Give boost serialization access to private members.

Definition at line 190 of file DmpContextual.hpp.

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

Public Member Functions

Protected Member Functions

Protected Attributes

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation