Crocoddyl
 
Loading...
Searching...
No Matches
solver-base.hpp
1
2// BSD 3-Clause License
3//
4// Copyright (C) 2019-2025, LAAS-CNRS, University of Edinburgh,
5// Heriot-Watt University
6// Copyright note valid unless otherwise stated in individual files.
7// All rights reserved.
9
10#ifndef CROCODDYL_CORE_SOLVER_BASE_HPP_
11#define CROCODDYL_CORE_SOLVER_BASE_HPP_
12
13#include "crocoddyl/core/fwd.hpp"
14#include "crocoddyl/core/optctrl/shooting.hpp"
15#include "crocoddyl/core/utils/stop-watch.hpp"
16
17namespace crocoddyl {
18
19class CallbackAbstract; // forward declaration
20static std::vector<Eigen::VectorXd> DEFAULT_VECTOR;
21
22enum FeasibilityNorm { LInf = 0, L1 };
23
61 public:
62 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
63
69 explicit SolverAbstract(std::shared_ptr<ShootingProblem> problem);
70 virtual ~SolverAbstract();
71
92 virtual bool solve(
93 const std::vector<Eigen::VectorXd>& init_xs = DEFAULT_VECTOR,
94 const std::vector<Eigen::VectorXd>& init_us = DEFAULT_VECTOR,
95 const std::size_t maxiter = 100, const bool is_feasible = false,
96 const double reg_init = NAN) = 0;
97
114 virtual void computeDirection(const bool recalc) = 0;
115
128 virtual double tryStep(const double steplength = 1) = 0;
129
138 virtual double stoppingCriteria() = 0;
139
147 virtual const Eigen::Vector2d& expectedImprovement() = 0;
148
155 virtual void resizeData();
156
170
181
192
209 void setCandidate(
210 const std::vector<Eigen::VectorXd>& xs_warm = DEFAULT_VECTOR,
211 const std::vector<Eigen::VectorXd>& us_warm = DEFAULT_VECTOR,
212 const bool is_feasible = false);
213
222 void setCallbacks(
223 const std::vector<std::shared_ptr<CallbackAbstract> >& callbacks);
224
228 const std::vector<std::shared_ptr<CallbackAbstract> >& getCallbacks() const;
229
233 const std::shared_ptr<ShootingProblem>& get_problem() const;
234
238 const std::vector<Eigen::VectorXd>& get_xs() const;
239
243 const std::vector<Eigen::VectorXd>& get_us() const;
244
248 const std::vector<Eigen::VectorXd>& get_fs() const;
249
254 bool get_is_feasible() const;
255
259 double get_cost() const;
260
264 double get_merit() const;
265
269 double get_stop() const;
270
274 const Eigen::Vector2d& get_d() const;
275
279 double get_dV() const;
280
284 double get_dPhi() const;
285
290 double get_dVexp() const;
291
296 double get_dPhiexp() const;
297
301 double get_dfeas() const;
302
306 double get_feas() const;
307
311 double get_ffeas() const;
312
316 double get_gfeas() const;
317
321 double get_hfeas() const;
322
326 double get_ffeas_try() const;
327
331 double get_gfeas_try() const;
332
336 double get_hfeas_try() const;
337
341 double get_preg() const;
342
346 double get_dreg() const;
347
348 DEPRECATED("Use get_preg for primal-variable regularization",
349 double get_xreg() const;)
350 DEPRECATED("Use get_preg for primal-variable regularization",
351 double get_ureg() const;)
352
356 double get_steplength() const;
357
361 double get_th_acceptstep() const;
362
366 double get_th_stop() const;
367
371 double get_th_gaptol() const;
372
377 FeasibilityNorm get_feasnorm() const;
378
382 std::size_t get_iter() const;
383
387 void set_xs(const std::vector<Eigen::VectorXd>& xs);
388
392 void set_us(const std::vector<Eigen::VectorXd>& us);
393
397 void set_preg(const double preg);
398
402 void set_dreg(const double dreg);
403
404 DEPRECATED("Use set_preg for primal-variable regularization",
405 void set_xreg(const double xreg);)
406 DEPRECATED("Use set_preg for primal-variable regularization",
407 void set_ureg(const double ureg);)
408
412 void set_th_acceptstep(const double th_acceptstep);
413
417 void set_th_stop(const double th_stop);
418
422 void set_th_gaptol(const double th_gaptol);
423
428 void set_feasnorm(const FeasibilityNorm feas_norm);
429
430 protected:
431 std::shared_ptr<ShootingProblem> problem_;
432 std::vector<Eigen::VectorXd> xs_;
433 std::vector<Eigen::VectorXd> us_;
434 std::vector<Eigen::VectorXd> fs_;
435 std::vector<std::shared_ptr<CallbackAbstract> >
440 double cost_;
441 double merit_;
442 double stop_;
443 Eigen::Vector2d d_;
444 double dV_;
445 double dPhi_;
446 double dVexp_;
447 double dPhiexp_;
448 double dfeas_;
449 double feas_;
450 double
452 double gfeas_;
454 double hfeas_;
456 double ffeas_try_;
458 double gfeas_try_;
460 double hfeas_try_;
462 double preg_;
463 double dreg_;
464 DEPRECATED("Use preg_ for primal-variable regularization",
465 double xreg_;)
466 DEPRECATED("Use dreg_ for primal-variable regularization",
467 double ureg_;)
468 double steplength_;
470 double th_stop_;
471 double th_gaptol_;
472 enum FeasibilityNorm feasnorm_;
474 std::size_t iter_;
475 double tmp_feas_;
476 std::vector<Eigen::VectorXd> g_adj_;
477};
478
487 public:
492 virtual ~CallbackAbstract() {}
493
499 virtual void operator()(SolverAbstract& solver) = 0;
500};
501
502bool raiseIfNaN(const double value);
503
504} // namespace crocoddyl
505
506#endif // CROCODDYL_CORE_SOLVER_BASE_HPP_
Abstract class for solver callbacks.
CallbackAbstract()
Initialize the callback function.
virtual void operator()(SolverAbstract &solver)=0
Run the callback function given a solver.
Abstract class for optimal control solvers.
double get_cost() const
Return the cost for the current guess.
std::vector< Eigen::VectorXd > g_adj_
Adjusted inequality bound.
double get_dPhi() const
Return the reduction in the merit function .
double get_th_gaptol() const
Return the threshold for accepting a gap as non-zero.
double dVexp_
Expected reduction in the cost function.
std::vector< Eigen::VectorXd > xs_
State trajectory.
std::size_t get_iter() const
Return the number of iterations performed by the solver.
double get_hfeas() const
Return the equality feasibility for the current guess.
void set_th_stop(const double th_stop)
Modify the tolerance for stopping the algorithm.
double stop_
Value computed by stoppingCriteria()
void set_xs(const std::vector< Eigen::VectorXd > &xs)
Modify the state trajectory .
double get_dVexp() const
Return the expected reduction in the cost function .
double dreg_
Current dual-variable regularization value.
double feas_
Total feasibility for the current guess.
bool is_feasible_
Label that indicates is the iteration is feasible.
std::shared_ptr< ShootingProblem > problem_
optimal control problem
std::vector< Eigen::VectorXd > us_
Control trajectory.
double get_dPhiexp() const
Return the expected reduction in the merit function .
double th_acceptstep_
Threshold used for accepting step.
double get_steplength() const
Return the step length .
void set_th_gaptol(const double th_gaptol)
Modify the threshold for accepting a gap as non-zero.
double get_merit() const
Return the merit for the current guess.
virtual const Eigen::Vector2d & expectedImprovement()=0
Return the expected improvement from a given current search direction .
double dPhi_
Reduction in the merit function computed by tryStep()
const std::vector< std::shared_ptr< CallbackAbstract > > & getCallbacks() const
Return the list of callback functions using for diagnostic.
double computeInequalityFeasibility()
Compute the feasibility of the inequality constraints for the current guess.
double get_preg() const
Return the primal-variable regularization.
double get_hfeas_try() const
Return the equality feasibility for the current step length.
double th_stop_
Tolerance for stopping the algorithm.
double computeDynamicFeasibility()
Compute the dynamic feasibility for the current guess .
virtual void computeDirection(const bool recalc)=0
Compute the search direction for the current guess .
const Eigen::Vector2d & get_d() const
Return the linear and quadratic terms of the expected improvement.
double dPhiexp_
Expected reduction in the merit function.
enum FeasibilityNorm feasnorm_
void setCandidate(const std::vector< Eigen::VectorXd > &xs_warm=DEFAULT_VECTOR, const std::vector< Eigen::VectorXd > &us_warm=DEFAULT_VECTOR, const bool is_feasible=false)
Set the solver candidate trajectories .
double get_th_stop() const
Return the tolerance for stopping the algorithm.
double dfeas_
Reduction in the feasibility.
void set_feasnorm(const FeasibilityNorm feas_norm)
Modify the current norm used for computed the dynamic and constraint feasibility.
double get_ffeas() const
Return the dynamic feasibility for the current guess.
double get_gfeas() const
Return the inequality feasibility for the current guess.
double cost_
Cost for the current guess.
std::vector< std::shared_ptr< CallbackAbstract > > callbacks_
Callback functions.
virtual double tryStep(const double steplength=1)=0
Try a predefined step length and compute its cost improvement .
void set_us(const std::vector< Eigen::VectorXd > &us)
Modify the control trajectory .
double steplength_
< Current control regularization values
void setCallbacks(const std::vector< std::shared_ptr< CallbackAbstract > > &callbacks)
Set a list of callback functions using for the solver diagnostic.
double th_gaptol_
Threshold limit to check non-zero gaps.
std::size_t iter_
Number of iteration performed by the solver.
double get_feas() const
Return the total feasibility for the current guess.
double dV_
Reduction in the cost function computed by tryStep()
double get_stop() const
Return the stopping-criteria value computed by stoppingCriteria()
double get_ffeas_try() const
Return the dynamic feasibility for the current step length.
void set_dreg(const double dreg)
Modify the dual-variable regularization value.
Eigen::Vector2d d_
LQ approximation of the expected improvement.
double get_dV() const
Return the reduction in the cost function .
const std::vector< Eigen::VectorXd > & get_fs() const
Return the dynamic infeasibility .
const std::vector< Eigen::VectorXd > & get_xs() const
Return the state trajectory .
double get_dfeas() const
Return the reduction in the feasibility.
void set_preg(const double preg)
Modify the primal-variable regularization value.
double ffeas_
Feasibility of the dynamic constraints for the current guess.
double get_gfeas_try() const
Return the inequality feasibility for the current step length.
bool get_is_feasible() const
Return the feasibility status of the trajectory.
double preg_
Current primal-variable regularization value.
const std::vector< Eigen::VectorXd > & get_us() const
Return the control trajectory .
double merit_
Merit for the current guess.
virtual void resizeData()
Resizing the solver data.
virtual bool solve(const std::vector< Eigen::VectorXd > &init_xs=DEFAULT_VECTOR, const std::vector< Eigen::VectorXd > &init_us=DEFAULT_VECTOR, const std::size_t maxiter=100, const bool is_feasible=false, const double reg_init=NAN)=0
Compute the optimal trajectory as lists of and terms.
std::vector< Eigen::VectorXd > fs_
Gaps/defects between shooting nodes.
virtual double stoppingCriteria()=0
Return a positive value that quantifies the algorithm termination.
void set_th_acceptstep(const double th_acceptstep)
Modify the threshold used for accepting step.
const std::shared_ptr< ShootingProblem > & get_problem() const
Return the shooting problem.
double tmp_feas_
Temporal variables used for computed the feasibility.
double get_th_acceptstep() const
Return the threshold used for accepting a step.
FeasibilityNorm get_feasnorm() const
Return the type of norm used to evaluate the dynamic and constraints feasibility.
double get_dreg() const
Return the dual-variable regularization.
double computeEqualityFeasibility()
Compute the feasibility of the equality constraints for the current guess.