| Directory: | ./ |
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| File: | include/crocoddyl/core/numdiff/action.hpp |
| Date: | 2025-01-30 11:01:55 |
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| 1 | /////////////////////////////////////////////////////////////////////////////// | ||
| 2 | // BSD 3-Clause License | ||
| 3 | // | ||
| 4 | // Copyright (C) 2019-2024, LAAS-CNRS, New York University, | ||
| 5 | // Max Planck Gesellschaft, University of Edinburgh, | ||
| 6 | // Heriot-Watt University | ||
| 7 | // Copyright note valid unless otherwise stated in individual files. | ||
| 8 | // All rights reserved. | ||
| 9 | /////////////////////////////////////////////////////////////////////////////// | ||
| 10 | |||
| 11 | #ifndef CROCODDYL_CORE_NUMDIFF_ACTION_HPP_ | ||
| 12 | #define CROCODDYL_CORE_NUMDIFF_ACTION_HPP_ | ||
| 13 | |||
| 14 | #include <vector> | ||
| 15 | |||
| 16 | #include "crocoddyl/core/action-base.hpp" | ||
| 17 | #include "crocoddyl/core/fwd.hpp" | ||
| 18 | |||
| 19 | namespace crocoddyl { | ||
| 20 | |||
| 21 | /** | ||
| 22 | * @brief This class computes the numerical differentiation of an action model. | ||
| 23 | * | ||
| 24 | * It computes the Jacobian of the cost, its residual and dynamics via numerical | ||
| 25 | * differentiation. It considers that the action model owns a cost residual and | ||
| 26 | * the cost is the square of this residual, i.e., | ||
| 27 | * \f$\ell(\mathbf{x},\mathbf{u})=\frac{1}{2}\|\mathbf{r}(\mathbf{x},\mathbf{u})\|^2\f$, | ||
| 28 | * where \f$\mathbf{r}(\mathbf{x},\mathbf{u})\f$ is the residual vector. The | ||
| 29 | * Hessian is computed only through the Gauss-Newton approximation, i.e., | ||
| 30 | * \f{eqnarray*}{ | ||
| 31 | * \mathbf{\ell}_\mathbf{xx} &=& \mathbf{R_x}^T\mathbf{R_x} \\ | ||
| 32 | * \mathbf{\ell}_\mathbf{uu} &=& \mathbf{R_u}^T\mathbf{R_u} \\ | ||
| 33 | * \mathbf{\ell}_\mathbf{xu} &=& \mathbf{R_x}^T\mathbf{R_u} | ||
| 34 | * \f} | ||
| 35 | * where the Jacobians of the cost residuals are denoted by \f$\mathbf{R_x}\f$ | ||
| 36 | * and \f$\mathbf{R_u}\f$. Note that this approximation ignores the tensor | ||
| 37 | * products (e.g., \f$\mathbf{R_{xx}}\mathbf{r}\f$). | ||
| 38 | * | ||
| 39 | * Finally, in the case that the cost does not have a residual, we set the | ||
| 40 | * Hessian to zero, i.e., \f$\mathbf{L_{xx}} = \mathbf{L_{xu}} = \mathbf{L_{uu}} | ||
| 41 | * = \mathbf{0}\f$. | ||
| 42 | * | ||
| 43 | * \sa `ActionModelAbstractTpl()`, `calcDiff()` | ||
| 44 | */ | ||
| 45 | template <typename _Scalar> | ||
| 46 | class ActionModelNumDiffTpl : public ActionModelAbstractTpl<_Scalar> { | ||
| 47 | public: | ||
| 48 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 49 | |||
| 50 | typedef _Scalar Scalar; | ||
| 51 | typedef ActionDataAbstractTpl<Scalar> ActionDataAbstract; | ||
| 52 | typedef ActionModelAbstractTpl<Scalar> Base; | ||
| 53 | typedef ActionDataNumDiffTpl<Scalar> Data; | ||
| 54 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 55 | typedef typename MathBaseTpl<Scalar>::VectorXs VectorXs; | ||
| 56 | typedef typename MathBaseTpl<Scalar>::MatrixXs MatrixXs; | ||
| 57 | |||
| 58 | /** | ||
| 59 | * @brief Initialize the numdiff action model | ||
| 60 | * | ||
| 61 | * @param[in] model Action model that we want to apply the | ||
| 62 | * numerical differentiation | ||
| 63 | * @param[in] with_gauss_approx True if we want to use the Gauss | ||
| 64 | * approximation for computing the Hessians | ||
| 65 | */ | ||
| 66 | explicit ActionModelNumDiffTpl(std::shared_ptr<Base> model, | ||
| 67 | bool with_gauss_approx = false); | ||
| 68 | virtual ~ActionModelNumDiffTpl(); | ||
| 69 | |||
| 70 | /** | ||
| 71 | * @brief @copydoc Base::calc() | ||
| 72 | */ | ||
| 73 | virtual void calc(const std::shared_ptr<ActionDataAbstract>& data, | ||
| 74 | const Eigen::Ref<const VectorXs>& x, | ||
| 75 | const Eigen::Ref<const VectorXs>& u); | ||
| 76 | |||
| 77 | /** | ||
| 78 | * @brief @copydoc Base::calc(const std::shared_ptr<ActionDataAbstract>& | ||
| 79 | * data, const Eigen::Ref<const VectorXs>& x) | ||
| 80 | */ | ||
| 81 | virtual void calc(const std::shared_ptr<ActionDataAbstract>& data, | ||
| 82 | const Eigen::Ref<const VectorXs>& x); | ||
| 83 | |||
| 84 | /** | ||
| 85 | * @brief @copydoc Base::calcDiff() | ||
| 86 | */ | ||
| 87 | virtual void calcDiff(const std::shared_ptr<ActionDataAbstract>& data, | ||
| 88 | const Eigen::Ref<const VectorXs>& x, | ||
| 89 | const Eigen::Ref<const VectorXs>& u); | ||
| 90 | |||
| 91 | /** | ||
| 92 | * @brief @copydoc Base::calcDiff(const std::shared_ptr<ActionDataAbstract>& | ||
| 93 | * data, const Eigen::Ref<const VectorXs>& x) | ||
| 94 | */ | ||
| 95 | virtual void calcDiff(const std::shared_ptr<ActionDataAbstract>& data, | ||
| 96 | const Eigen::Ref<const VectorXs>& x); | ||
| 97 | |||
| 98 | /** | ||
| 99 | * @brief @copydoc Base::createData() | ||
| 100 | */ | ||
| 101 | virtual std::shared_ptr<ActionDataAbstract> createData(); | ||
| 102 | |||
| 103 | /** | ||
| 104 | * @brief @copydoc Base::quasiStatic() | ||
| 105 | */ | ||
| 106 | virtual void quasiStatic(const std::shared_ptr<ActionDataAbstract>& data, | ||
| 107 | Eigen::Ref<VectorXs> u, | ||
| 108 | const Eigen::Ref<const VectorXs>& x, | ||
| 109 | const std::size_t maxiter = 100, | ||
| 110 | const Scalar tol = Scalar(1e-9)); | ||
| 111 | |||
| 112 | /** | ||
| 113 | * @brief Return the acton model that we use to numerical differentiate | ||
| 114 | */ | ||
| 115 | const std::shared_ptr<Base>& get_model() const; | ||
| 116 | |||
| 117 | /** | ||
| 118 | * @brief Return the disturbance constant used in the numerical | ||
| 119 | * differentiation routine | ||
| 120 | */ | ||
| 121 | const Scalar get_disturbance() const; | ||
| 122 | |||
| 123 | /** | ||
| 124 | * @brief Modify the disturbance constant used in the numerical | ||
| 125 | * differentiation routine | ||
| 126 | */ | ||
| 127 | void set_disturbance(const Scalar disturbance); | ||
| 128 | |||
| 129 | /** | ||
| 130 | * @brief Identify if the Gauss approximation is going to be used or not. | ||
| 131 | */ | ||
| 132 | bool get_with_gauss_approx(); | ||
| 133 | |||
| 134 | /** | ||
| 135 | * @brief Print relevant information of the diff-action numdiff model | ||
| 136 | * | ||
| 137 | * @param[out] os Output stream object | ||
| 138 | */ | ||
| 139 | virtual void print(std::ostream& os) const; | ||
| 140 | |||
| 141 | protected: | ||
| 142 | using Base::has_control_limits_; //!< Indicates whether any of the control | ||
| 143 | //!< limits | ||
| 144 | using Base::nr_; //!< Dimension of the cost residual | ||
| 145 | using Base::nu_; //!< Control dimension | ||
| 146 | using Base::state_; //!< Model of the state | ||
| 147 | using Base::u_lb_; //!< Lower control limits | ||
| 148 | using Base::u_ub_; //!< Upper control limits | ||
| 149 | |||
| 150 | private: | ||
| 151 | /** | ||
| 152 | * @brief Make sure that when we finite difference the Action Model, the user | ||
| 153 | * does not face unknown behaviour because of the finite differencing of a | ||
| 154 | * quaternion around pi. This behaviour might occur if CostModelState and | ||
| 155 | * FloatingInContact differential model are used together. | ||
| 156 | * | ||
| 157 | * For full discussions see issue | ||
| 158 | * https://gepgitlab.laas.fr/loco-3d/crocoddyl/issues/139 | ||
| 159 | * | ||
| 160 | * @param x is the state at which the check is performed. | ||
| 161 | */ | ||
| 162 | void assertStableStateFD(const Eigen::Ref<const VectorXs>& x); | ||
| 163 | |||
| 164 | std::shared_ptr<Base> model_; //!< Action model hat we want to apply the | ||
| 165 | //!< numerical differentiation | ||
| 166 | Scalar e_jac_; //!< Constant used for computing disturbances in Jacobian | ||
| 167 | //!< calculation | ||
| 168 | Scalar e_hess_; //!< Constant used for computing disturbances in Hessian | ||
| 169 | //!< calculation | ||
| 170 | bool with_gauss_approx_; //!< True if we want to use the Gauss approximation | ||
| 171 | //!< for computing the Hessians | ||
| 172 | }; | ||
| 173 | |||
| 174 | template <typename _Scalar> | ||
| 175 | struct ActionDataNumDiffTpl : public ActionDataAbstractTpl<_Scalar> { | ||
| 176 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 177 | |||
| 178 | typedef _Scalar Scalar; | ||
| 179 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 180 | typedef ActionDataAbstractTpl<Scalar> Base; | ||
| 181 | typedef typename MathBaseTpl<Scalar>::VectorXs VectorXs; | ||
| 182 | typedef typename MathBaseTpl<Scalar>::MatrixXs MatrixXs; | ||
| 183 | |||
| 184 | /** | ||
| 185 | * @brief Initialize the numdiff action data | ||
| 186 | * | ||
| 187 | * @tparam Model is the type of the `ActionModelAbstractTpl`. | ||
| 188 | * @param model is the object to compute the numerical differentiation from. | ||
| 189 | */ | ||
| 190 | template <template <typename Scalar> class Model> | ||
| 191 | 270 | explicit ActionDataNumDiffTpl(Model<Scalar>* const model) | |
| 192 | : Base(model), | ||
| 193 |
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270 | Rx(model->get_model()->get_nr(), |
| 194 | 270 | model->get_model()->get_state()->get_ndx()), | |
| 195 |
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270 | Ru(model->get_model()->get_nr(), model->get_model()->get_nu()), |
| 196 |
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270 | dx(model->get_model()->get_state()->get_ndx()), |
| 197 |
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270 | du(model->get_model()->get_nu()), |
| 198 |
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540 | xp(model->get_model()->get_state()->get_nx()) { |
| 199 |
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270 | Rx.setZero(); |
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270 | Ru.setZero(); |
| 201 |
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270 | dx.setZero(); |
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270 | du.setZero(); |
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270 | xp.setZero(); |
| 204 | |||
| 205 | 270 | const std::size_t ndx = model->get_model()->get_state()->get_ndx(); | |
| 206 | 270 | const std::size_t nu = model->get_model()->get_nu(); | |
| 207 |
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270 | data_0 = model->get_model()->createData(); |
| 208 |
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11573 | for (std::size_t i = 0; i < ndx; ++i) { |
| 209 |
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11303 | data_x.push_back(model->get_model()->createData()); |
| 210 | } | ||
| 211 |
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7548 | for (std::size_t i = 0; i < nu; ++i) { |
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7278 | data_u.push_back(model->get_model()->createData()); |
| 213 | } | ||
| 214 | 270 | } | |
| 215 | |||
| 216 | using Base::cost; | ||
| 217 | using Base::Fu; | ||
| 218 | using Base::Fx; | ||
| 219 | using Base::Lu; | ||
| 220 | using Base::Luu; | ||
| 221 | using Base::Lx; | ||
| 222 | using Base::Lxu; | ||
| 223 | using Base::Lxx; | ||
| 224 | using Base::r; | ||
| 225 | using Base::xnext; | ||
| 226 | |||
| 227 | Scalar x_norm; //!< Norm of the state vector | ||
| 228 | Scalar | ||
| 229 | xh_jac; //!< Disturbance value used for computing \f$ \ell_\mathbf{x} \f$ | ||
| 230 | Scalar | ||
| 231 | uh_jac; //!< Disturbance value used for computing \f$ \ell_\mathbf{u} \f$ | ||
| 232 | Scalar xh_hess; //!< Disturbance value used for computing \f$ | ||
| 233 | //!< \ell_\mathbf{xx} \f$ | ||
| 234 | Scalar uh_hess; //!< Disturbance value used for computing \f$ | ||
| 235 | //!< \ell_\mathbf{uu} \f$ | ||
| 236 | Scalar xh_hess_pow2; | ||
| 237 | Scalar uh_hess_pow2; | ||
| 238 | Scalar xuh_hess_pow2; | ||
| 239 | MatrixXs Rx; //!< Cost residual jacobian: \f$ \frac{d r(x,u)}{dx} \f$ | ||
| 240 | MatrixXs Ru; //!< Cost residual jacobian: \f$ \frac{d r(x,u)}{du} \f$ | ||
| 241 | VectorXs dx; //!< State disturbance | ||
| 242 | VectorXs du; //!< Control disturbance | ||
| 243 | VectorXs xp; //!< The integrated state from the disturbance on one DoF "\f$ | ||
| 244 | //!< \int x dx_i \f$" | ||
| 245 | std::shared_ptr<Base> data_0; //!< The data that contains the final results | ||
| 246 | std::vector<std::shared_ptr<Base> > | ||
| 247 | data_x; //!< The temporary data associated with the state variation | ||
| 248 | std::vector<std::shared_ptr<Base> > | ||
| 249 | data_u; //!< The temporary data associated with the control variation | ||
| 250 | }; | ||
| 251 | |||
| 252 | } // namespace crocoddyl | ||
| 253 | |||
| 254 | /* --- Details -------------------------------------------------------------- */ | ||
| 255 | /* --- Details -------------------------------------------------------------- */ | ||
| 256 | /* --- Details -------------------------------------------------------------- */ | ||
| 257 | #include "crocoddyl/core/numdiff/action.hxx" | ||
| 258 | |||
| 259 | #endif // CROCODDYL_CORE_NUMDIFF_ACTION_HPP_ | ||
| 260 |