Inheritance diagram for SolverBoxDDP:

Public Member Functions
EIGEN_MAKE_ALIGNED_OPERATOR_NEW	DEPRECATED ("Do not use SolverBoxDDP. Instead, you should use SolverBoxFDDP(problem, " "DynamicsSolverType::SingleShoot)", explicit SolverBoxDDP(std::shared_ptr< ShootingProblem > problem) :SolverBoxFDDP(problem){}) virtual ~SolverBoxDDP()=default
Public Member Functions inherited from SolverBoxFDDPTpl< double >
	SolverBoxFDDPTpl (std::shared_ptr< ShootingProblem > problem, const DynamicsSolverType dyn_solver=FeasShoot, const EqualitySolverType term_solver=LuNull)
SolverBoxFDDPTpl< NewScalar >	cast () const
	Cast the Box-FDDP solver to a different scalar type.
virtual void	computePolicy (const std::size_t t) override
	Compute the feedforward and feedback terms (control policy) computed via a Cholesky decomposition.
virtual void	forwardPass (const Scalar steplength)
const std::vector< MatrixXs > &	get_Quu_inv () const
Public Member Functions inherited from SolverFDDPTpl< double >
	SolverFDDPTpl (std::shared_ptr< ShootingProblem > problem, const DynamicsSolverType dyn_solver=FeasShoot, const EqualitySolverType term_solver=LuNull)
	Initialize the FDDP solver.
virtual void	backwardPass ()
	Run the backward pass (Riccati sweep).
void	batchPass ()
	Run the batch pass to account for its constraints.
SolverFDDPTpl< NewScalar >	cast () const
	Cast the FDDP solver to a different scalar type.
virtual bool	checkAcceptance () override
	Check if we should accept or not the step.
virtual void	computeActionValueFunction (const std::size_t t, const std::shared_ptr< ActionModelAbstract > &model, const std::shared_ptr< ActionDataAbstract > &data)
	Compute the linear-quadratic approximation of the control action-value function.
virtual void	computeBatchActionValueFunction (const std::size_t t, const std::shared_ptr< ActionDataAbstract > &data)
	Compute the linear-quadratic approximation of the control action-value function associated to the batch's constraints.
virtual void	computeBatchPolicy (const std::size_t t)
	Compute the feedforward and feedback terms (control policy) associated to the batch's constraints.
virtual void	computeBatchValueFunction (const std::size_t t)
	Compute the linear-quadratic approximation of the value function associated to the batch's constraints.
virtual void	computeCandidate (const Scalar step_length=Scalar(1.)) override
	Compute new candidate solution using step length.
virtual void	computeDirection (const bool recalc=true) override
	Compute the search direction $(\delta\mathbf{x}^k,\delta\mathbf{u}^k)$ for the current guess $(\mathbf{x}^k_s,\mathbf{u}^k_s)$ .
Scalar	computeDynamicFeasibility ()
	Compute the dynamic feasibility $\\|\mathbf{f}_{\mathbf{s}}\\|_{\infty,1}$ for the current guess $(\mathbf{x}^k,\mathbf{u}^k)$ .
Scalar	computeEqualityFeasibility ()
	Compute the feasibility of the equality constraints for the current guess.
virtual void	computeExpectedMeritFunctionImprovement () override
	Compute the expected merit function improvement for the current step.
Scalar	computeFeasibility (const std::vector< VectorXs > &fs)
	Compute the feasibility from a given residual vector.
Scalar	computeInequalityFeasibility ()
	Compute the feasibility of the inequality constraints for the current guess.
virtual void	computeMeritFunctionImprovement () override
	Compute the merit function improvement for the current step.
virtual void	computeValueFunction (const std::size_t t, const std::shared_ptr< ActionModelAbstract > &model)
	Compute the linear-quadratic approximation of the value function.
void	decreaseRegularization () override
	Decrease the state and control regularization values by a regfactor_ factor.
bool	decreaseRegularizationCriteria () override
	Criteria used to decrease regularization.
virtual Vector3s	expectedImprovement () override
	Return the expected improvement $dV_{exp}$ from a given current search direction $(\delta\mathbf{x}^k,\delta\mathbf{u}^k)$ .
virtual void	feasShootForwardPass (const Scalar steplength)
	Run the feasibility-driven nonlinear rollout.
void	forwardPass (const Scalar steplength=Scalar(1.))
	Perform a forward pass with a predefined step length.
const VectorXs &	get_beta_plus () const
	Return the next terminal-constraint multiplier $\boldsymbol{\beta}^+$ .
const MatrixXs &	get_dHc () const
	Return the Jacobian of the terminal constraint gains $\delta\mathbf{H}_{c}$ .
const std::vector< MatrixXs > &	get_dUc () const
	Return the linear update in $\delta\mathbf{U}_{c_s}$ .
const std::vector< MatrixXs > &	get_dXc () const
	Return the linear update in $\delta\mathbf{X}_{c_s}$ .
DynamicsSolverType	get_dynamics_solver () const
	Return the type of solver used for handling the dynamics constraints.
const VectorXs &	get_hc () const
	Return the bias term of the terminal constraint gains $\mathbf{h}_{c}$ .
const std::vector< MatrixXsRowMajor > &	get_K () const
	Return the feedback gains $\mathbf{K}_{s}$ .
const std::vector< VectorXs > &	get_k () const
	Return the feedforward gains $\mathbf{k}_{s}$ .
const std::vector< MatrixXs > &	get_Kc () const
	Return the feedforward gains $\mathbf{K}_{c_s}$ .
const std::vector< VectorXs > &	get_Qu () const
	Return the Jacobian of the Hamiltonian function $\mathbf{Q}_{\mathbf{u}_s}$ .
const std::vector< MatrixXs > &	get_Quc () const
	Return the Hessian of the Hamiltonian function $\mathbf{Q}_{\mathbf{uc}_s}$ .
const std::vector< MatrixXs > &	get_Quu () const
	Return the Hessian of the Hamiltonian function $\mathbf{Q}_{\mathbf{uu}_s}$ .
const std::vector< VectorXs > &	get_Qx () const
	Return the Jacobian of the Hamiltonian function $\mathbf{Q}_{\mathbf{x}_s}$ .
const std::vector< MatrixXs > &	get_Qxc () const
	Return the Hessian of the Hamiltonian function $\mathbf{Q}_{\mathbf{xc}_s}$ .
const std::vector< MatrixXs > &	get_Qxu () const
	Return the Hessian of the Hamiltonian function $\mathbf{Q}_{\mathbf{xu}_s}$ .
const std::vector< MatrixXs > &	get_Qxx () const
	Return the Hessian of the Hamiltonian function $\mathbf{Q}_{\mathbf{xx}_s}$ .
Scalar	get_reg_decfactor () const
	Return the regularization factor used to decrease the damping value.
Scalar	get_reg_incfactor () const
	Return the regularization factor used to increase the damping value.
Scalar	get_rho () const
	Return the rho parameter used in the merit function.
EqualitySolverType	get_terminal_solver () const
	Return the type of solver used for handling the terminal constraints.
Scalar	get_th_acceptminstep () const
	Return the threshold used for accepting minimum steps.
Scalar	get_th_acceptnegstep () const
	Return the threshold used for accepting step along ascent direction.
Scalar	get_th_grad () const
	Return the tolerance of the expected gradient used for testing the step.
Scalar	get_th_minfeas () const
	Return the threshold for switching to feasibility.
Scalar	get_th_minimprove () const
	Return the minimum improvement threshold used to increase regularization.
Scalar	get_th_stepdec () const
	Return the step-length threshold used to decrease regularization.
Scalar	get_th_stepinc () const
	Return the step-length threshold used to increase regularization.
const std::vector< std::size_t > &	get_Ts () const
	Return the hybrid shooting intervals.
Scalar	get_upsilon () const
	Return the estimated penalty parameter that balances relative contribution of the cost function and equality constraints.
Scalar	get_upsilon_decfactor () const
	Return the upsilon decresing factor used to estimate to balance optimality and feasibility.
const std::vector< VectorXs > &	get_Vx () const
	Return the Hessian of the Value function $V_{\mathbf{x}_s}$ .
const std::vector< MatrixXs > &	get_Vxc () const
	Return the Hessian of the Value function $V_{\mathbf{xc}_s}$ .
const std::vector< MatrixXs > &	get_Vxx () const
	Return the Hessian of the Value function $V_{\mathbf{xx}_s}$ .
bool	get_zero_upsilon () const
	Return the zero-upsilon label.
virtual void	hybridShootForwardPass (const Scalar steplength)
	Run the multiple-shooting rollout with intervals of feasibility-driven search.
void	increaseRegularization () override
	Increase the state and control regularization values by a regfactor_ factor.
bool	increaseRegularizationCriteria () override
	Criteria used to increase regularization.
void	linearRollout ()
	Perform a linear rollout give the current control policy.
virtual void	multiShootForwardPass (const Scalar steplength)
	Run the multiple-shooting rollout.
virtual void	resizeData ()
	Resizing the solver data.
void	set_dynamics_solver (const DynamicsSolverType type, const std::size_t Tshoot=0)
	Set the dynamic solver used for handling the dynamics constraints.
void	set_reg_decfactor (const Scalar reg_factor)
	Modify the regularization factor used to decrease the damping value.
void	set_reg_incfactor (const Scalar reg_factor)
	Modify the regularization factor used to increase the damping value.
void	set_rho (const Scalar rho)
	Modify the rho parameter used in the merit function.
void	set_terminal_solver (const EqualitySolverType type)
	Set the type of solver used for handling the terminal constraints.
void	set_th_acceptminstep (const Scalar th_acceptminstep)
	Modify the threshold used for accepting minimum steps.
void	set_th_acceptnegstep (const Scalar th_acceptnegstep)
	Modify the threshold used for accepting step along ascent direction.
void	set_th_grad (const Scalar th_grad)
	Modify the tolerance of the expected gradient used for testing the step.
void	set_th_minfeas (const Scalar th_minfeas)
	Modify the threshold for switching to feasibility.
void	set_th_minimprove (const Scalar th_step)
	Modify the minimum improvement threshold used to increase regularization.
void	set_th_noimprovement (const Scalar th_noimprovement)
	Modify the threshold used to accept steps that cannot be be improved due to numerical errors the th noimprovement object.
void	set_th_stepdec (const Scalar th_step)
	Modify the step-length threshold used to decrease regularization.
void	set_th_stepinc (const Scalar th_step)
	Modify the step-length threshold used to increase regularization.
void	set_upsilon_decfactor (const Scalar th_step)
	Modify the upsilon decresing factor used to estimate to balance optimality and feasibility.
void	set_zero_upsilon (const bool zero_upsilon)
	Modify the zero-upsilon label.
virtual void	singleShootForwardPass (const Scalar steplength)
	Run the classical nonlinear rollout.
virtual Scalar	stoppingCriteria () override
	Return a positive value that quantifies the algorithm termination.
void	updateCandidate () override
	Update the candidate solution: cost, feasibilities, and merit value.
void	updateDir ()
	Update search direction associated with the batch's constraints.
virtual void	updateDualsAndSlacks (const Scalar stepLength=Scalar(1.))
	Update the dual and slack variables with a predefined step length.
virtual void	updateMeritFunction () override
	Update the merit function value for the current guess.
Public Member Functions inherited from SolverAbstractTpl< double >
	SolverAbstractTpl (std::shared_ptr< ShootingProblem > problem)
	Initialize the solver.
virtual void	calcDir ()
	Refresh the linearization of the optimal control problem around the current candidate.
Scalar	computeControlFeasibility (const std::vector< VectorXs > &us)
	Compute the control box-constraint feasibility from a given control trajectory.
Scalar	computeDynamicFeasibility ()
	Compute the dynamic feasibility $\\|\mathbf{f}_{\mathbf{s}}\\|_{\infty,1}$ for the current guess $(\mathbf{x}^k,\mathbf{u}^k)$ .
Scalar	computeEqualityFeasibility ()
	Compute the feasibility of the equality constraints for the current guess.
Scalar	computeFeasibility (const std::vector< VectorXs > &fs)
	Compute the feasibility from a given residual vector.
Scalar	computeInequalityFeasibility ()
	Compute the feasibility of the inequality constraints for the current guess.
Scalar	computeStateFeasibility (const std::vector< VectorXs > &xs)
	Compute the state box-constraint feasibility from a given state trajectory.
	DEPRECATED ("Do not use this threshold. It is not needed by our solvers", Scalar get_th_gaptol() const { return th_gaptol_;}) FeasibilityNorm get_feasnorm() const
	Return the threshold for accepting a gap as non-zero.
	DEPRECATED ("Do not use this threshold. It is not needed by our solvers", void set_th_gaptol(const Scalar th_gaptol);) void set_feasnorm(const FeasibilityNorm feas_norm)
	Modify the threshold for accepting a gap as non-zero.
	DEPRECATED ("Use get_preg for primal-variable regularization", Scalar get_xreg() const { return preg_;}) DEPRECATED("Use get_preg for primal-variable regularization"
	DEPRECATED ("Use set_preg for primal-variable regularization", void set_xreg(const Scalar xreg) { if(xreg< Scalar(0.)) { throw_pretty("Invalid argument: "<< "xreg value has to be positive.");} xreg_=xreg;preg_=xreg;}) DEPRECATED("Use set_preg for primal-variable regularization"
const std::vector< Scalar > &	get_alphas () const
	Return the set of step lengths using by the line-search procedure.
Scalar	get_cost () const
	Return the cost for the current guess.
Scalar	get_dfeas () const
	Return the reduction in the feasibility.
Scalar	get_dPhi () const
	Return the reduction in the merit function $\Delta\Phi$ .
Scalar	get_dPhiexp () const
	Return the expected reduction in the merit function $\Delta\Phi_{exp}$ .
Scalar	get_dreg () const
	Return the dual-variable regularization.
const std::vector< VectorXs > &	get_dus () const
	Return the feedforward gains $\delta\mathbf{u}_s$ .
const Vector3s &	get_DV () const
	Return the constant, linear, and quadratic terms of the expected improvement.
Scalar	get_dV () const
	Return the reduction in the cost function $\Delta V$ .
Scalar	get_dVexp () const
	Return the expected reduction in the cost function $\Delta V_{exp}$ .
const std::vector< VectorXs > &	get_dxs () const
	Return the linear update in $\delta\mathbf{x}_s$ .
Scalar	get_feas () const
	Return the total feasibility for the current guess.
Scalar	get_ffeas () const
	Return the dynamic feasibility for the current guess.
Scalar	get_ffeas_try () const
	Return the dynamic feasibility for the current step length.
const std::vector< VectorXs > &	get_fs () const
	Return the dynamic infeasibility $\mathbf{f}_{s}$ .
const std::vector< VectorXs > &	get_fs_try () const
	Return the trail dynamic infeasibility $\mathbf{f}_{s}$ .
Scalar	get_gfeas () const
	Return the inequality feasibility for the current guess.
Scalar	get_gfeas_try () const
	Return the inequality feasibility for the current step length.
Scalar	get_hfeas () const
	Return the equality feasibility for the current guess.
Scalar	get_hfeas_try () const
	Return the equality feasibility for the current step length.
bool	get_is_feasible () const
	Return the feasibility status of the $(\mathbf{x}_s,\mathbf{u}_s)$ trajectory.
std::size_t	get_iter () const
	Return the number of iterations performed by the solver.
Scalar	get_merit () const
	Return the merit for the current guess.
Scalar	get_preg () const
	Return the primal-variable regularization.
const std::shared_ptr< ShootingProblem > &	get_problem () const
	Return the shooting problem.
Scalar	get_reg_max () const
	Return the maximum regularization value.
Scalar	get_reg_min () const
	Return the minimum regularization value.
Scalar	get_steplength () const
	Return the step length $\alpha$ .
Scalar	get_stop () const
	Return the stopping-criteria value computed by stoppingCriteria().
Scalar	get_th_acceptstep () const
	Return the threshold used for accepting a step.
Scalar	get_th_stop () const
	Return the tolerance for stopping the algorithm.
Scalar	get_ureg () const
const std::vector< VectorXs > &	get_us () const
	Return the control trajectory $\mathbf{u}_s$ .
const std::vector< VectorXs > &	get_us_try () const
	Return the trial control trajectory $\mathbf{u}_s$ .
const std::vector< VectorXs > &	get_xs () const
	Return the state trajectory $\mathbf{x}_s$ .
const std::vector< VectorXs > &	get_xs_try () const
	Return the trial state trajectory $\mathbf{x}_s$ .
const std::vector< std::shared_ptr< CallbackAbstract > > &	getCallbacks () const
	Return the list of callback functions using for diagnostic.
void	set_alphas (const std::vector< Scalar > &alphas)
	Modify the set of step lengths using by the line-search procedure.
void	set_dreg (const Scalar dreg)
	Modify the dual-variable regularization value.
void	set_preg (const Scalar preg)
	Modify the primal-variable regularization value.
void	set_reg_max (const Scalar regmax)
	Modify the maximum regularization value.
void	set_reg_min (const Scalar regmin)
	Modify the minimum regularization value.
void	set_th_acceptstep (const Scalar th_acceptstep)
	Modify the threshold used for accepting step.
void	set_th_stop (const Scalar th_stop)
	Modify the tolerance for stopping the algorithm.
void	set_ureg (const Scalar ureg)
void	set_us (const std::vector< VectorXs > &us)
	Modify the control trajectory $\mathbf{u}_s$ .
void	set_xs (const std::vector< VectorXs > &xs)
	Modify the state trajectory $\mathbf{x}_s$ .
void	setCallbacks (const std::vector< std::shared_ptr< CallbackAbstract > > &callbacks)
	Set a list of callback functions using for the solver diagnostic.
virtual void	setCandidate (const std::vector< VectorXs > &xs_warm=DefaultVector< Scalar >::value, const std::vector< VectorXs > &us_warm=DefaultVector< Scalar >::value, const bool is_feasible=false)
	Set the solver candidate trajectories $(\mathbf{x}_s,\mathbf{u}_s)$ .
virtual bool	solve (const std::vector< VectorXs > &init_xs=DefaultVector< Scalar >::value, const std::vector< VectorXs > &init_us=DefaultVector< Scalar >::value, const std::size_t maxiter=100, const bool is_feasible=false, const Scalar reg_init=std::numeric_limits< Scalar >::quiet_NaN())
	Compute the optimal trajectory $\mathbf{x}^_s,\mathbf{u}^_s$ as lists of and terms.
virtual Scalar	tryStep (const Scalar steplength=Scalar(1.))
	Try a predefined step length $\alpha$ and compute its cost improvement and merit improvement $d\Phi$ .

Additional Inherited Members
Public Types inherited from SolverBoxFDDPTpl< double >
typedef ShootingProblem::ActionDataAbstract	ActionDataAbstract
typedef ShootingProblem::ActionModelAbstract	ActionModelAbstract
typedef BoxQPTpl< Scalar >	BoxQP
typedef BoxQPSolutionTpl< Scalar >	BoxQPSolution
typedef MathBaseTpl< Scalar >	MathBase
typedef MathBase::MatrixXs	MatrixXs
typedef ShootingProblemTpl< Scalar >	ShootingProblem
typedef SolverFDDPTpl< Scalar >	SolverFDDP
typedef MathBase::VectorXs	VectorXs
Public Types inherited from SolverFDDPTpl< double >
typedef ShootingProblem::ActionDataAbstract	ActionDataAbstract
typedef ShootingProblem::ActionModelAbstract	ActionModelAbstract
typedef CallbackAbstractTpl< Scalar >	CallbackAbstract
typedef MathBaseTpl< Scalar >	MathBase
typedef MathBase::MatrixXs	MatrixXs
typedef MathBase::MatrixXsRowMajor	MatrixXsRowMajor
typedef ShootingProblemTpl< Scalar >	ShootingProblem
typedef SolverAbstractTpl< Scalar >	SolverAbstract
typedef MathBase::Vector3s	Vector3s
typedef MathBase::VectorXs	VectorXs
Public Types inherited from SolverAbstractTpl< double >
typedef ShootingProblem::ActionDataAbstract	ActionDataAbstract
typedef ShootingProblem::ActionModelAbstract	ActionModelAbstract
typedef CallbackAbstractTpl< Scalar >	CallbackAbstract
typedef MathBaseTpl< Scalar >	MathBase
typedef ShootingProblemTpl< Scalar >	ShootingProblem
typedef MathBase::Vector3s	Vector3s
typedef MathBase::VectorXs	VectorXs
Public Attributes inherited from SolverBoxFDDPTpl< double >
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef double	Scalar
Public Attributes inherited from SolverFDDPTpl< double >
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef double	Scalar
Public Attributes inherited from SolverAbstractTpl< double >
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef double	Scalar
Protected Member Functions inherited from SolverBoxFDDPTpl< double >
void	allocateData ()
virtual void	resizeRunningData () override
	Resize data associated with the running models of the shooting problem.
Protected Member Functions inherited from SolverFDDPTpl< double >
void	allocateData ()
	Allocate all the internal data needed for the solver.
void	computeNullTerminalMultiplier ()
	compute the multiplier associated to the terminal constraint
virtual void	resizeTerminalData () override
	Resize data associated with the terminal model of the shooting problem.
Protected Member Functions inherited from SolverAbstractTpl< double >
void	allocateData ()
	Allocate all the basic data needed in solvers.
	DEPRECATED ("Do not use this threshold. It is not needed by our solvers", Scalar th_gaptol_;) enum FeasibilityNorm feasnorm_
	DEPRECATED ("Use preg_ for primal-variable regularization", Scalar xreg_;) DEPRECATED("Use dreg_ for primal-variable regularization"
Protected Attributes inherited from SolverBoxFDDPTpl< double >
std::vector< VectorXs >	du_lb_
std::vector< VectorXs >	du_ub_
std::vector< VectorXs >	dx_
	State error during the roll-out/forward-pass (size T).
DynamicsSolverType	dyn_solver_
	Type of dynamics solver.
std::vector< MatrixXsRowMajor >	K_
	Feedback gains $\mathbf{K}$ .
std::vector< VectorXs >	k_
	Feed-forward terms $\mathbf{l}$ .
BoxQP	qp_
std::vector< VectorXs >	Qu_
	Gradient of the Hamiltonian $\mathbf{Q_u}$ .
std::vector< MatrixXs >	Quu_
	Hessian of the Hamiltonian $\mathbf{Q_{uu}}$ .
std::vector< MatrixXs >	Quu_inv_
std::vector< MatrixXs >	Qxu_
	Hessian of the Hamiltonian $\mathbf{Q_{xu}}$ .
Scalar	reg_decfactor_
Scalar	reg_incfactor_
Scalar	rho_
EqualitySolverType	term_solver_
	Type of terminal solver.
Scalar	th_acceptminstep_
Scalar	th_acceptnegstep_
Scalar	th_grad_
Scalar	th_minfeas_
	Threshold for switching to feasibility.
Scalar	th_minimprove_
Scalar	th_noimprovement_
Scalar	th_stepdec_
	Step-length threshold used to decrease regularization.
Scalar	th_stepinc_
	Step-length threshold used to increase regularization.
Scalar	upsilon_decfactor_
std::vector< VectorXs >	Vx_
	Gradient of the Value function $\mathbf{V_x}$ .
std::vector< MatrixXs >	Vxx_
	Hessian of the Value function $\mathbf{V_{xx}}$ .
VectorXs	xnext_
	Next state $\mathbf{x}^{'}$ .
bool	zero_upsilon_
Protected Attributes inherited from SolverFDDPTpl< double >
std::vector< VectorXs >	dx_
	State error during the roll-out/forward-pass (size T).
DynamicsSolverType	dyn_solver_
	Type of dynamics solver.
VectorXs	fTVxx_p_
std::vector< MatrixXsRowMajor >	FuTVxx_p_
std::vector< MatrixXsRowMajor >	FxTVxx_p_
std::vector< MatrixXsRowMajor >	K_
	Feedback gains $\mathbf{K}$ .
std::vector< VectorXs >	k_
	Feed-forward terms $\mathbf{l}$ .
std::vector< VectorXs >	Luu_du_
std::vector< VectorXs >	Lxu_du_
std::vector< VectorXs >	Lxx_dx_
std::vector< VectorXs >	Qu_
	Gradient of the Hamiltonian $\mathbf{Q_u}$ .
std::vector< MatrixXs >	Quu_
	Hessian of the Hamiltonian $\mathbf{Q_{uu}}$ .
std::vector< Eigen::LLT< MatrixXs > >	Quu_llt_
	Cholesky LLT solver.
std::vector< VectorXs >	Qx_
	Gradient of the Hamiltonian $\mathbf{Q_x}$ .
std::vector< MatrixXs >	Qxu_
	Hessian of the Hamiltonian $\mathbf{Q_{xu}}$ .
std::vector< MatrixXs >	Qxx_
	Hessian of the Hamiltonian $\mathbf{Q_{xx}}$ .
Scalar	reg_decfactor_
Scalar	reg_incfactor_
Scalar	rho_
EqualitySolverType	term_solver_
	Type of terminal solver.
Scalar	th_acceptminstep_
Scalar	th_acceptnegstep_
Scalar	th_grad_
Scalar	th_minfeas_
	Threshold for switching to feasibility.
Scalar	th_minimprove_
Scalar	th_noimprovement_
Scalar	th_stepdec_
	Step-length threshold used to decrease regularization.
Scalar	th_stepinc_
	Step-length threshold used to increase regularization.
std::vector< std::size_t >	Ts_
	Index that describes the hybrid shoots.
Scalar	upsilon_
Scalar	upsilon_decfactor_
std::vector< VectorXs >	Vx_
	Gradient of the Value function $\mathbf{V_x}$ .
std::vector< MatrixXs >	Vxx_
	Hessian of the Value function $\mathbf{V_{xx}}$ .
std::vector< VectorXs >	Vxx_f_
MatrixXs	Vxx_tmp_
	Temporary variable for ensuring symmetry of Vxx.
bool	zero_upsilon_
Protected Attributes inherited from SolverAbstractTpl< double >
bool	acceptstep_
std::vector< Scalar >	alphas_
	Set of step lengths using by the line-search procedure.
std::vector< std::shared_ptr< CallbackAbstract > >	callbacks_
	Callback functions.
Scalar	cost_
	Cost for the current guess.
Scalar	cost_try_
	Total cost computed by line-search procedure.
Scalar	dfeas_
	Reduction in the feasibility.
Scalar	dImpr_
Scalar	dPhi_
	Reduction in the merit function computed by tryStep().
Scalar	dPhiexp_
Scalar	dreg_
	Current dual-variable regularization value.
std::vector< VectorXs >	dus_
	Linear control direction (size T).
Vector3s	DV_
	LQ approximation of the expected improvement.
Scalar	dV_
	Reduction in the cost function computed by tryStep().
Scalar	dVexp_
Scalar	dVexp_full_
std::vector< VectorXs >	dxs_
	Linear state direction (size T + 1).
Scalar	feas_
	Total feasibility for the current guess.
Scalar	ffeas_
	Feasibility of the dynamic constraints for the current guess.
Scalar	ffeas_try_
std::vector< VectorXs >	fs_
	Dynamics gaps in each node.
std::vector< VectorXs >	fs_try_
std::vector< VectorXs >	g_adj_
	Adjusted inequality bound.
Scalar	gfeas_
Scalar	gfeas_try_
Scalar	hfeas_
Scalar	hfeas_try_
bool	is_feasible_
	Label that indicates is the iteration is feasible.
std::size_t	iter_
	Number of iteration performed by the solver.
Scalar	merit_
	Merit for the current guess.
std::size_t	ng_T_
	Dimension of termianl inequality constraints.
std::size_t	nh_T_
	Dimension of terminal equality constraints.
Scalar	preg_
	Current primal-variable regularization value.
std::shared_ptr< ShootingProblem >	problem_
	optimal control problem
bool	recalcdir_
Scalar	reg_max_
	Maximum allowed regularization value.
Scalar	reg_min_
	< Current control regularization values
Scalar	steplength_
	Current applied step length.
Scalar	stop_
	Value computed by stoppingCriteria().
Scalar	th_acceptstep_
	Threshold used for accepting step.
Scalar	th_stop_
	Tolerance for stopping the algorithm.
Scalar	tmp_feas_
	Temporal variables used for computed the feasibility.
std::vector< VectorXs >	u_adj_
	Adjusted control bound.
Scalar	ureg_
std::vector< VectorXs >	us_
	Control trajectory.
std::vector< VectorXs >	us_try_
	Control trajectory computed by line-search procedure.
bool	was_feasible_
std::vector< VectorXs >	x_adj_
	Adjusted state bound.
std::vector< VectorXs >	xs_
	State trajectory.
std::vector< VectorXs >	xs_try_
	State trajectory computed by line-search procedure.