11 #include "crocoddyl/core/solvers/box-ddp.hpp"
12 #include "crocoddyl/core/utils/exception.hpp"
16 SolverBoxDDP::SolverBoxDDP(boost::shared_ptr<ShootingProblem> problem)
17 : SolverDDP(problem), qp_(problem->get_runningModels()[0]->get_nu(), 100, 0.1, 1e-5, 0.) {
20 const std::size_t n_alphas = 10;
21 alphas_.resize(n_alphas);
22 for (std::size_t n = 0; n < n_alphas; ++n) {
23 alphas_[n] = 1. / pow(2.,
static_cast<double>(n));
32 SolverBoxDDP::~SolverBoxDDP() {}
34 void SolverBoxDDP::allocateData() {
35 SolverDDP::allocateData();
37 const std::size_t T = problem_->get_T();
39 const std::size_t nu = problem_->get_nu_max();
40 for (std::size_t t = 0; t < T; ++t) {
41 Quu_inv_[t] = Eigen::MatrixXd::Zero(nu, nu);
47 void SolverBoxDDP::computeGains(
const std::size_t t) {
48 const std::size_t nu = problem_->get_runningModels()[t]->get_nu();
50 if (!problem_->get_runningModels()[t]->get_has_control_limits() || !is_feasible_) {
52 SolverDDP::computeGains(t);
56 du_lb_.head(nu) = problem_->get_runningModels()[t]->get_u_lb() - us_[t].head(nu);
57 du_ub_.head(nu) = problem_->get_runningModels()[t]->get_u_ub() - us_[t].head(nu);
60 qp_.solve(Quu_[t].topLeftCorner(nu, nu), Qu_[t].head(nu), du_lb_.head(nu), du_ub_.head(nu), k_[t].head(nu));
63 Quu_inv_[t].topLeftCorner(nu, nu).setZero();
64 for (std::size_t i = 0; i < boxqp_sol.
free_idx.size(); ++i) {
65 for (std::size_t j = 0; j < boxqp_sol.
free_idx.size(); ++j) {
69 K_[t].topRows(nu).noalias() = Quu_inv_[t].topLeftCorner(nu, nu) * Qxu_[t].leftCols(nu).transpose();
70 k_[t].topRows(nu) = -boxqp_sol.
x;
74 for (std::size_t i = 0; i < boxqp_sol.
clamped_idx.size(); ++i) {
80 void SolverBoxDDP::forwardPass(
double steplength) {
81 if (steplength > 1. || steplength < 0.) {
82 throw_pretty(
"Invalid argument: "
83 <<
"invalid step length, value is between 0. to 1.");
86 xnext_ = problem_->get_x0();
87 const std::size_t T = problem_->get_T();
88 const std::vector<boost::shared_ptr<ActionModelAbstract> >& models = problem_->get_runningModels();
89 const std::vector<boost::shared_ptr<ActionDataAbstract> >& datas = problem_->get_runningDatas();
90 for (std::size_t t = 0; t < T; ++t) {
91 const boost::shared_ptr<ActionModelAbstract>& m = models[t];
92 const boost::shared_ptr<ActionDataAbstract>& d = datas[t];
93 const std::size_t nu = m->get_nu();
96 m->get_state()->diff(xs_[t], xs_try_[t], dx_[t]);
98 us_try_[t].head(nu).noalias() = us_[t].head(nu) - k_[t].head(nu) * steplength - K_[t].topRows(nu) * dx_[t];
99 if (m->get_has_control_limits()) {
100 us_try_[t].head(nu) = us_try_[t].head(nu).cwiseMax(m->get_u_lb()).cwiseMin(m->get_u_ub());
102 m->calc(d, xs_try_[t], us_try_[t].head(nu));
104 m->calc(d, xs_try_[t]);
107 cost_try_ += d->cost;
109 if (raiseIfNaN(cost_try_)) {
110 throw_pretty(
"forward_error");
112 if (raiseIfNaN(xnext_.lpNorm<Eigen::Infinity>())) {
113 throw_pretty(
"forward_error");
117 const boost::shared_ptr<ActionModelAbstract>& m = problem_->get_terminalModel();
118 const boost::shared_ptr<ActionDataAbstract>& d = problem_->get_terminalData();
119 if ((is_feasible_) || (steplength == 1)) {
120 xs_try_.back() = xnext_;
122 m->get_state()->integrate(xnext_, fs_.back() * (steplength - 1), xs_try_.back());
124 m->calc(d, xs_try_.back());
125 cost_try_ += d->cost;
127 if (raiseIfNaN(cost_try_)) {
128 throw_pretty(
"forward_error");
132 const std::vector<Eigen::MatrixXd>& SolverBoxDDP::get_Quu_inv()
const {
return Quu_inv_; }
std::vector< size_t > free_idx
Free space indexes.
Eigen::MatrixXd Hff_inv
Inverse of the free space Hessian.
Eigen::VectorXd x
Decision vector.
std::vector< size_t > clamped_idx
Clamped space indexes.