This class encapsulates a shooting problem. More...

#include <shooting.hpp>

Public Types
typedef ActionDataAbstractTpl< Scalar >	ActionDataAbstract

typedef ActionModelAbstractTpl< Scalar >	ActionModelAbstract

typedef MathBaseTpl< Scalar >	MathBase

typedef MathBase::VectorXs	VectorXs

Public Member Functions
	ShootingProblemTpl (const ShootingProblemTpl< Scalar > &problem)
	Initialize the shooting problem.

	ShootingProblemTpl (const VectorXs &x0, const std::vector< boost::shared_ptr< ActionModelAbstract > > &running_models, boost::shared_ptr< ActionModelAbstract > terminal_model)
	Initialize the shooting problem and allocate its data. More...

	ShootingProblemTpl (const VectorXs &x0, const std::vector< boost::shared_ptr< ActionModelAbstract > > &running_models, boost::shared_ptr< ActionModelAbstract > terminal_model, const std::vector< boost::shared_ptr< ActionDataAbstract > > &running_datas, boost::shared_ptr< ActionDataAbstract > terminal_data)
	Initialize the shooting problem (models and datas) More...

Scalar	calc (const std::vector< VectorXs > &xs, const std::vector< VectorXs > &us)
	Compute the cost and the next states. More...

Scalar	calcDiff (const std::vector< VectorXs > &xs, const std::vector< VectorXs > &us)
	Compute the derivatives of the cost and dynamics. More...

void	circularAppend (boost::shared_ptr< ActionModelAbstract > model)
	Circular append of the model and data onto the end running node. More...

void	circularAppend (boost::shared_ptr< ActionModelAbstract > model, boost::shared_ptr< ActionDataAbstract > data)
	Circular append of the model and data onto the end running node. More...

std::size_t	get_ndx () const
	Return the dimension of the tangent space of the state manifold.

std::size_t	get_nx () const
	Return the dimension of the state tuple.

const std::vector< boost::shared_ptr< ActionDataAbstract > > &	get_runningDatas () const
	Return the running datas.

const std::vector< boost::shared_ptr< ActionModelAbstract > > &	get_runningModels () const
	Return the running models.

std::size_t	get_T () const
	Return the number of running nodes.

const boost::shared_ptr< ActionDataAbstract > &	get_terminalData () const
	Return the terminal data.

const boost::shared_ptr< ActionModelAbstract > &	get_terminalModel () const
	Return the terminal model.

const VectorXs &	get_x0 () const
	Return the initial state.

DEPRECATED("Compute yourself the maximum dimension of the control vector", std::size_t get_nu_max() const ;) std bool	is_updated ()
	Return the maximum dimension of the control vector. More...

void	quasiStatic (std::vector< VectorXs > &us, const std::vector< VectorXs > &xs)
	Compute the quasic static commands given a state trajectory. More...

std::vector< VectorXs >	quasiStatic_xs (const std::vector< VectorXs > &xs)
	Compute the quasic static commands given a state trajectory. More...

void	rollout (const std::vector< VectorXs > &us, std::vector< VectorXs > &xs)
	Integrate the dynamics given a control sequence. More...

std::vector< VectorXs >	rollout_us (const std::vector< VectorXs > &us)
	Integrate the dynamics given a control sequence. More...

void	set_nthreads (const int nthreads)
	Modify the number of threads using with multithreading support. More...

void	set_runningModels (const std::vector< boost::shared_ptr< ActionModelAbstract > > &models)
	Modify the running models and allocate new data.

void	set_terminalModel (boost::shared_ptr< ActionModelAbstract > model)
	Modify the terminal model and allocate new data.

void	set_x0 (const VectorXs &x0_in)
	Modify the initial state.

void	updateModel (const std::size_t i, boost::shared_ptr< ActionModelAbstract > model)
	Update a model and allocated new data for a specific node. More...

void	updateNode (const std::size_t i, boost::shared_ptr< ActionModelAbstract > model, boost::shared_ptr< ActionDataAbstract > data)
	Update the model and data for a specific node. More...

Public Attributes
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef _Scalar	Scalar

Protected Attributes
Scalar	cost_
	Total cost.

bool	is_updated_

std::size_t	ndx_
	State rate dimension.

std::size_t	nthreads_

std::size_t	nu_max_
	Maximum control dimension.

std::size_t	nx_
	State dimension.

std::vector< boost::shared_ptr< ActionDataAbstract > >	running_datas_
	Running action data.

std::vector< boost::shared_ptr< ActionModelAbstract > >	running_models_
	Running action model.

std::size_t	T_
	number of running nodes

boost::shared_ptr< ActionDataAbstract >	terminal_data_
	Terminal action data.

boost::shared_ptr< ActionModelAbstract >	terminal_model_
	Terminal action model.

VectorXs	x0_
	Initial state.

Friends
template<class Scalar >
std::ostream &	operator<< (std::ostream &os, const ShootingProblemTpl< Scalar > &problem)
	Print information on the 'ShootingProblem'.

Detailed Description

template<typename _Scalar>
class crocoddyl::ShootingProblemTpl< _Scalar >

This class encapsulates a shooting problem.

A shooting problem encapsulates the initial state \(\mathbf{x}_{0}\in\mathcal{M}\), a set of running action models and a terminal action model for a discretized trajectory into \(T\) nodes. It has three main methods - calc, calcDiff and rollout. The first computes the set of next states and cost values per each node \(k\). Instead, calcDiff updates the derivatives of all action models. Finally, rollout integrates the system dynamics. This class is used to decouple problem formulation and resolution.

Definition at line 35 of file shooting.hpp.

Constructor & Destructor Documentation

◆ ShootingProblemTpl() [1/2]

ShootingProblemTpl	(	const VectorXs &	x0,
		const std::vector< boost::shared_ptr< ActionModelAbstract > > &	running_models,
		boost::shared_ptr< ActionModelAbstract >	terminal_model
	)

Initialize the shooting problem and allocate its data.

Parameters

[in]	x0	Initial state
[in]	running_models	Running action models (size \(T\))
[in]	terminal_model	Terminal action model

◆ ShootingProblemTpl() [2/2]

ShootingProblemTpl	(	const VectorXs &	x0,
		const std::vector< boost::shared_ptr< ActionModelAbstract > > &	running_models,
		boost::shared_ptr< ActionModelAbstract >	terminal_model,
		const std::vector< boost::shared_ptr< ActionDataAbstract > > &	running_datas,
		boost::shared_ptr< ActionDataAbstract >	terminal_data
	)

Initialize the shooting problem (models and datas)

Parameters

[in]	x0	Initial state
[in]	running_models	Running action models (size \(T\))
[in]	terminal_model	Terminal action model
[in]	running_datas	Running action datas (size \(T\))
[in]	terminal_data	Terminal action data

Member Function Documentation

◆ calc()

Scalar calc	(	const std::vector< VectorXs > &	xs,
		const std::vector< VectorXs > &	us
	)

Compute the cost and the next states.

For each node \(k\), and along the state \(\mathbf{x_{s}}\) and control \(\mathbf{u_{s}}\) trajectory, it computes the next state \(\mathbf{x}_{k+1}\) and cost \(l_{k}\).

Parameters

[in]	xs	time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))
[in]	us	time-discrete control sequence \(\mathbf{u_{s}}\) (size \(T\))

Returns: The total cost value \(l_{k}\)

◆ calcDiff()

Scalar calcDiff	(	const std::vector< VectorXs > &	xs,
		const std::vector< VectorXs > &	us
	)

Compute the derivatives of the cost and dynamics.

For each node \(k\), and along the state \(\mathbf{x_{s}}\) and control \(\mathbf{u_{s}}\) trajectory, it computes the derivatives of the cost \((\mathbf{l}_{\mathbf{x}}, \mathbf{l}_{\mathbf{u}}, \mathbf{l}_{\mathbf{xx}}, \mathbf{l}_{\mathbf{xu}}, \mathbf{l}_{\mathbf{uu}})\) and dynamics \((\mathbf{f}_{\mathbf{x}}, \mathbf{f}_{\mathbf{u}})\).

Parameters

[in]	xs	time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))
[in]	us	time-discrete control sequence \(\mathbf{u_{s}}\) (size \(T\))

Returns: The total cost value \(l_{k}\)

◆ rollout()

void rollout	(	const std::vector< VectorXs > &	us,
		std::vector< VectorXs > &	xs
	)

Integrate the dynamics given a control sequence.

Parameters

[in]	xs	time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))
[in]	us	time-discrete control sequence \(\mathbf{u_{s}}\) (size \(T\))

◆ rollout_us()

std::vector<VectorXs> rollout_us ( const std::vector< VectorXs > & us )

Integrate the dynamics given a control sequence.

Parameters

[in] us time-discrete control sequence \(\mathbf{u_{s}}\) (size \(T\))

Returns: the time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))

◆ quasiStatic()

void quasiStatic	(	std::vector< VectorXs > &	us,
		const std::vector< VectorXs > &	xs
	)

Compute the quasic static commands given a state trajectory.

Parameters

[out]	us	time-discrete control sequence \(\mathbf{u_{s}}\) (size \(T\))
[in]	xs	time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))

◆ quasiStatic_xs()

std::vector<VectorXs> quasiStatic_xs ( const std::vector< VectorXs > & xs )

Compute the quasic static commands given a state trajectory.

Parameters

[in] xs time-discrete state trajectory \(\mathbf{x_{s}}\) (size \(T+1\))

Returns: the time-discrete quasic static commands \(\mathbf{u_{s}}\) (size \(T\))

◆ circularAppend() [1/2]

void circularAppend	(	boost::shared_ptr< ActionModelAbstract >	model,
		boost::shared_ptr< ActionDataAbstract >	data
	)

Circular append of the model and data onto the end running node.

Once we update the end running node, the first running mode is removed as in a circular buffer.

Parameters

[in]	model	action model
[in]	data	action data

◆ circularAppend() [2/2]

void circularAppend ( boost::shared_ptr< ActionModelAbstract > model )

Circular append of the model and data onto the end running node.

Once we update the end running node, the first running mode is removed as in a circular buffer. Note that this method allocates new data for the end running node.

Parameters

[in] model action model

◆ updateNode()

void updateNode	(	const std::size_t	i,
		boost::shared_ptr< ActionModelAbstract >	model,
		boost::shared_ptr< ActionDataAbstract >	data
	)

Update the model and data for a specific node.

Parameters

[in]	i	node index \((0\leq i \lt T+1)\)
[in]	model	action model
[in]	data	action data

◆ updateModel()

void updateModel	(	const std::size_t	i,
		boost::shared_ptr< ActionModelAbstract >	model
	)

Update a model and allocated new data for a specific node.

Parameters

[in]	i	node index \((0\leq i \lt T+1)\)
[in]	model	action model

◆ set_nthreads()

void set_nthreads ( const int nthreads )

Modify the number of threads using with multithreading support.

For values lower than 1, the number of threads is chosen by CROCODDYL_WITH_NTHREADS macro

◆ is_updated()

DEPRECATED ("Compute yourself the maximum dimension of the control vector", std::size_t get_nu_max() const;) std bool is_updated ( )

Return the maximum dimension of the control vector.

Return the number of threads

Return only once true is the shooting problem has been changed, otherwise false

Member Data Documentation

◆ nthreads_

std::size_t nthreads_

protected

Number of threads launch by the multi-threading application

Definition at line 301 of file shooting.hpp.

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

/root/robotpkg/optimization/py-crocoddyl/work/crocoddyl-2.1.0/include/crocoddyl/core/fwd.hpp
/root/robotpkg/optimization/py-crocoddyl/work/crocoddyl-2.1.0/include/crocoddyl/core/optctrl/shooting.hpp

Public Types

Public Member Functions

Public Attributes

Protected Attributes

Friends

Detailed Description

template<typename _Scalar> class crocoddyl::ShootingProblemTpl< _Scalar >

Constructor & Destructor Documentation

◆ ShootingProblemTpl() [1/2]

◆ ShootingProblemTpl() [2/2]

Member Function Documentation

◆ calc()

◆ calcDiff()

◆ rollout()

◆ rollout_us()

◆ quasiStatic()

◆ quasiStatic_xs()

◆ circularAppend() [1/2]

◆ circularAppend() [2/2]

◆ updateNode()

◆ updateModel()

◆ set_nthreads()

◆ is_updated()

Member Data Documentation

◆ nthreads_

template<typename _Scalar>
class crocoddyl::ShootingProblemTpl< _Scalar >