The Stomp class. More...

#include <stomp.h>

Public Member Functions
bool	cancel ()
	Cancel optimization in progress. (Thread-Safe) This method is thead-safe. More...

bool	clear ()
	Resets all internal variables. More...

void	setConfig (const StompConfiguration &config)
	Sets the configuration and resets all internal variables. More...

bool	solve (const std::vector< double > &first, const std::vector< double > &last, Eigen::MatrixXd &parameters_optimized)
	Find the optimal solution provided a start and end goal. More...

bool	solve (const Eigen::VectorXd &first, const Eigen::VectorXd &last, Eigen::MatrixXd &parameters_optimized)
	Find the optimal solution provided a start and end goal. More...

bool	solve (const Eigen::MatrixXd &initial_parameters, Eigen::MatrixXd &parameters_optimized)
	Find the optimal solution provided an intial guess. More...

	Stomp (const StompConfiguration &config, TaskPtr task)
	Stomp Constructor. More...

Protected Member Functions
bool	computeInitialTrajectory (const std::vector< double > &first, const std::vector< double > &last)
	Computes an inital guess at a solution given a start and end state. More...

bool	computeNoisyRolloutsCosts ()
	Computes the total cost for each of the noisy rollouts. More...

bool	computeOptimizedCost ()
	Computes the optimized trajectory cost [Control Cost + State Cost] If the current cost is not less than the previous cost the parameters are reset to the previous iteration's parameters. More...

bool	computeProbabilities ()
	Computes the probability from the state cost at every timestep for each noisy rollout. More...

bool	computeRolloutsControlCosts ()
	Compute the control cost for each noisy rollout. This is the sum of the acceleration squared, then each noisy rollouts control cost is divided by the maximum control cost found amoung the noisy rollouts. More...

bool	computeRolloutsStateCosts ()
	Computes the cost at every timestep for each noisy rollout. More...

bool	filterNoisyRollouts ()
	Applies the optimization task's filter methods to the noisy trajectories. More...

bool	generateNoisyRollouts ()
	Generate a set of noisy rollouts. More...

bool	resetVariables ()
	Reset all internal variables. More...

bool	runSingleIteration ()
	Run a single iteration of the stomp algorithm. More...

bool	updateParameters ()
	Computes update from probabilities using convex combination. More...

Protected Attributes
StompConfiguration	config_
	Configuration parameters.

Eigen::MatrixXd	control_cost_matrix_R_
	A matrix [timesteps][timesteps], Referred to as 'R = A x A_transpose' in the literature.

Eigen::MatrixXd	control_cost_matrix_R_padded_
	The control cost matrix including padding.

unsigned int	current_iteration_
	Current iteration for the optimization.

double	current_lowest_cost_
	Hold the lowest cost of the optimized parameters.

Eigen::MatrixXd	finite_diff_matrix_A_padded_
	The finite difference matrix including padding.

Eigen::MatrixXd	inv_control_cost_matrix_R_
	A matrix [timesteps][timesteps], R^-1 ' matrix.

std::vector< Rollout >	noisy_rollouts_
	Holds the noisy rollouts.

int	num_active_rollouts_
	Number of active rollouts.

int	num_timesteps_padded_
	The number of timesteps to pad the optimization with: timesteps + 2*(FINITE_DIFF_RULE_LENGTH - 1)

Eigen::MatrixXd	parameters_control_costs_
	A matrix [dimensions][timesteps] of the parameters control costs.

Eigen::MatrixXd	parameters_optimized_
	A matrix [dimensions][timesteps] of the optimized parameters.

Eigen::VectorXd	parameters_state_costs_
	A vector [timesteps] of the parameters state costs.

double	parameters_total_cost_
	Total cost of the optimized parameters.

Eigen::MatrixXd	parameters_updates_
	A matrix [dimensions][timesteps] of the parameter updates.

bool	parameters_valid_
	whether or not the optimized parameters are valid

bool	parameters_valid_prev_
	whether or not the optimized parameters from the previous iteration are valid

std::atomic< bool >	proceed_
	Used to determine if the optimization has been cancelled.

std::vector< Rollout >	reused_rollouts_
	Used for reordering arrays based on cost.

int	start_index_padded_
	The index corresponding to the start of the non-paded section in the padded arrays.

TaskPtr	task_
	The task to be optimized.

Detailed Description

The Stomp class.

Definition at line 38 of file stomp.h.

Constructor & Destructor Documentation

stomp_core::Stomp::Stomp	(	const StompConfiguration &	config,
		TaskPtr	task
	)

Stomp Constructor.

Parameters

config	Stomp configuration parameters
task	The item to be optimized.

Definition at line 172 of file stomp.cpp.

Member Function Documentation

bool stomp_core::Stomp::cancel ( )

Cancel optimization in progress. (Thread-Safe) This method is thead-safe.

Returns: True if sucessful, otherwise false.

Definition at line 416 of file stomp.cpp.

bool stomp_core::Stomp::clear ( )

Resets all internal variables.

Returns: True if sucessful, otherwise false.

Definition at line 181 of file stomp.cpp.

bool stomp_core::Stomp::computeInitialTrajectory	(	const std::vector< double > &	first,
		const std::vector< double > &	last
	)

protected

Computes an inital guess at a solution given a start and end state.

Parameters

first	Start state for the task
last	Final state for the task

Returns: True if sucessful, otherwise false.

Definition at line 393 of file stomp.cpp.

bool stomp_core::Stomp::computeNoisyRolloutsCosts ( )

protected

Computes the total cost for each of the noisy rollouts.

Returns: True if sucessful, otherwise false.

Definition at line 564 of file stomp.cpp.

bool stomp_core::Stomp::computeOptimizedCost ( )

protected

Computes the optimized trajectory cost [Control Cost + State Cost] If the current cost is not less than the previous cost the parameters are reset to the previous iteration's parameters.

Returns

Definition at line 771 of file stomp.cpp.

bool stomp_core::Stomp::computeProbabilities ( )

protected

Computes the probability from the state cost at every timestep for each noisy rollout.

Returns: True if sucessful, otherwise false.

Definition at line 654 of file stomp.cpp.

bool stomp_core::Stomp::computeRolloutsControlCosts ( )

protected

Compute the control cost for each noisy rollout. This is the sum of the acceleration squared, then each noisy rollouts control cost is divided by the maximum control cost found amoung the noisy rollouts.

Returns: True if sucessful, otherwise false.

Definition at line 629 of file stomp.cpp.

bool stomp_core::Stomp::computeRolloutsStateCosts ( )

protected

Computes the cost at every timestep for each noisy rollout.

Returns: True if sucessful, otherwise false.

Definition at line 602 of file stomp.cpp.

bool stomp_core::Stomp::filterNoisyRollouts ( )

protected

Applies the optimization task's filter methods to the noisy trajectories.

Returns: True if sucessful, otherwise false.

Definition at line 538 of file stomp.cpp.

bool stomp_core::Stomp::generateNoisyRollouts ( )

protected

Generate a set of noisy rollouts.

Returns: True if sucessful, otherwise false.

Definition at line 443 of file stomp.cpp.

bool stomp_core::Stomp::resetVariables ( )

protected

Reset all internal variables.

Returns: True if sucessful, otherwise false.

Definition at line 299 of file stomp.cpp.

bool stomp_core::Stomp::runSingleIteration ( )

protected

Run a single iteration of the stomp algorithm.

Returns: True if it was able to succesfully perform a single iteration. False is returned when an error is encounter at one of the many optimization steps.

Definition at line 423 of file stomp.cpp.

void stomp_core::Stomp::setConfig ( const StompConfiguration & config )

Sets the configuration and resets all internal variables.

Parameters

config Stomp Configuration struct

Definition at line 186 of file stomp.cpp.

bool stomp_core::Stomp::solve	(	const std::vector< double > &	first,
		const std::vector< double > &	last,
		Eigen::MatrixXd &	parameters_optimized
	)

Find the optimal solution provided a start and end goal.

Parameters

first	Start state for the task
last	Final state for the task
parameters_optimized	Optimized solution [parameters][timesteps]

Returns: True if solution was found, otherwise false.

Definition at line 192 of file stomp.cpp.

bool stomp_core::Stomp::solve	(	const Eigen::VectorXd &	first,
		const Eigen::VectorXd &	last,
		Eigen::MatrixXd &	parameters_optimized
	)

Find the optimal solution provided a start and end goal.

Parameters

first	Start state for the task
last	Final state for the task
parameters_optimized	Optimized solution [Parameters][timesteps]

Returns: True if solution was found, otherwise false.

Definition at line 204 of file stomp.cpp.

bool stomp_core::Stomp::solve	(	const Eigen::MatrixXd &	initial_parameters,
		Eigen::MatrixXd &	parameters_optimized
	)

Find the optimal solution provided an intial guess.

Parameters

initial_parameters	A matrix [Parameters][timesteps]
parameters_optimized	The optimized solution [Parameters][timesteps]

Returns: True if solution was found, otherwise false.

Definition at line 217 of file stomp.cpp.

bool stomp_core::Stomp::updateParameters ( )

protected

Computes update from probabilities using convex combination.

Returns: True if sucessful, otherwise false.

Definition at line 743 of file stomp.cpp.

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

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation