| Directory: | ./ |
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| File: | include/crocoddyl/core/cost-base.hpp |
| Date: | 2025-03-26 19:23:43 |
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| 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. | ||
| 8 | /////////////////////////////////////////////////////////////////////////////// | ||
| 9 | |||
| 10 | #ifndef CROCODDYL_CORE_COST_BASE_HPP_ | ||
| 11 | #define CROCODDYL_CORE_COST_BASE_HPP_ | ||
| 12 | |||
| 13 | #include <memory> | ||
| 14 | |||
| 15 | #include "crocoddyl/core/activation-base.hpp" | ||
| 16 | #include "crocoddyl/core/activations/quadratic.hpp" | ||
| 17 | #include "crocoddyl/core/data-collector-base.hpp" | ||
| 18 | #include "crocoddyl/core/fwd.hpp" | ||
| 19 | #include "crocoddyl/core/residual-base.hpp" | ||
| 20 | #include "crocoddyl/core/state-base.hpp" | ||
| 21 | #include "crocoddyl/core/utils/deprecate.hpp" | ||
| 22 | |||
| 23 | namespace crocoddyl { | ||
| 24 | |||
| 25 | class CostModelBase { | ||
| 26 | public: | ||
| 27 | 15384 | virtual ~CostModelBase() = default; | |
| 28 | |||
| 29 | ✗ | CROCODDYL_BASE_CAST(CostModelBase, CostModelAbstractTpl) | |
| 30 | }; | ||
| 31 | |||
| 32 | /** | ||
| 33 | * @brief Abstract class for cost models | ||
| 34 | * | ||
| 35 | * A cost model is defined by the scalar activation function \f$a(\cdot)\f$ and | ||
| 36 | * by the residual function \f$\mathbf{r}(\cdot)\f$ as follows: \f[ | ||
| 37 | * \ell(\mathbf{x},\mathbf{u}) = a(\mathbf{r}(\mathbf{x}, \mathbf{u})), \f] | ||
| 38 | * where the residual function depends on the state point | ||
| 39 | * \f$\mathbf{x}\in\mathcal{X}\f$, which lies in the state manifold described | ||
| 40 | * with a `nx`-tuple, its velocity \f$\dot{\mathbf{x}}\in | ||
| 41 | * T_{\mathbf{x}}\mathcal{X}\f$ that belongs to the tangent space with `ndx` | ||
| 42 | * dimension, and the control input \f$\mathbf{u}\in\mathbb{R}^{nu}\f$. The | ||
| 43 | * residual vector is defined by \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ where `nr` | ||
| 44 | * describes its dimension in the Euclidean space. On the other hand, the | ||
| 45 | * activation function builds a cost value based on the definition of the | ||
| 46 | * residual vector. The residual vector has to be specialized in a derived | ||
| 47 | * classes. | ||
| 48 | * | ||
| 49 | * The main computations are carring out in `calc()` and `calcDiff()` routines. | ||
| 50 | * `calc()` computes the cost (and its residual) and `calcDiff()` computes the | ||
| 51 | * derivatives of the cost function (and its residual). Concretely speaking, | ||
| 52 | * `calcDiff()` builds a linear-quadratic approximation of the cost function | ||
| 53 | * with the form: \f$\mathbf{l_x}\in\mathbb{R}^{ndx}\f$, | ||
| 54 | * \f$\mathbf{l_u}\in\mathbb{R}^{nu}\f$, | ||
| 55 | * \f$\mathbf{l_{xx}}\in\mathbb{R}^{ndx\times ndx}\f$, | ||
| 56 | * \f$\mathbf{l_{xu}}\in\mathbb{R}^{ndx\times nu}\f$, | ||
| 57 | * \f$\mathbf{l_{uu}}\in\mathbb{R}^{nu\times nu}\f$ are the Jacobians and | ||
| 58 | * Hessians, respectively. Additionally, it is important to note that | ||
| 59 | * `calcDiff()` computes the derivatives using the latest stored values by | ||
| 60 | * `calc()`. Thus, we need to first run `calc()`. | ||
| 61 | * | ||
| 62 | * \sa `ActivationModelAbstractTpl`, `ResidualModelAbstractTpl` `calc()`, | ||
| 63 | * `calcDiff()`, `createData()` | ||
| 64 | */ | ||
| 65 | template <typename _Scalar> | ||
| 66 | class CostModelAbstractTpl : public CostModelBase { | ||
| 67 | public: | ||
| 68 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 69 | |||
| 70 | typedef _Scalar Scalar; | ||
| 71 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 72 | typedef CostDataAbstractTpl<Scalar> CostDataAbstract; | ||
| 73 | typedef StateAbstractTpl<Scalar> StateAbstract; | ||
| 74 | typedef ActivationModelAbstractTpl<Scalar> ActivationModelAbstract; | ||
| 75 | typedef ResidualModelAbstractTpl<Scalar> ResidualModelAbstract; | ||
| 76 | typedef ActivationModelQuadTpl<Scalar> ActivationModelQuad; | ||
| 77 | typedef DataCollectorAbstractTpl<Scalar> DataCollectorAbstract; | ||
| 78 | typedef typename MathBase::VectorXs VectorXs; | ||
| 79 | typedef typename MathBase::MatrixXs MatrixXs; | ||
| 80 | |||
| 81 | /** | ||
| 82 | * @brief Initialize the cost model | ||
| 83 | * | ||
| 84 | * @param[in] state State of the dynamical system | ||
| 85 | * @param[in] activation Activation model | ||
| 86 | * @param[in] residual Residual model | ||
| 87 | */ | ||
| 88 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 89 | std::shared_ptr<ActivationModelAbstract> activation, | ||
| 90 | std::shared_ptr<ResidualModelAbstract> residual); | ||
| 91 | |||
| 92 | /** | ||
| 93 | * @brief Initialize the cost model | ||
| 94 | * | ||
| 95 | * @param[in] state State of the dynamical system | ||
| 96 | * @param[in] activation Activation model | ||
| 97 | * @param[in] nu Dimension of control vector | ||
| 98 | */ | ||
| 99 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 100 | std::shared_ptr<ActivationModelAbstract> activation, | ||
| 101 | const std::size_t nu); | ||
| 102 | |||
| 103 | /** | ||
| 104 | * @copybrief CostModelAbstractTpl() | ||
| 105 | * | ||
| 106 | * The default `nu` value is obtained from `StateAbstractTpl::get_nv()`. | ||
| 107 | * | ||
| 108 | * @param[in] state State of the dynamical system | ||
| 109 | * @param[in] activation Activation model | ||
| 110 | */ | ||
| 111 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 112 | std::shared_ptr<ActivationModelAbstract> activation); | ||
| 113 | |||
| 114 | /** | ||
| 115 | * @copybrief CostModelAbstractTpl() | ||
| 116 | * | ||
| 117 | * We use `ActivationModelQuadTpl` as a default activation model (i.e., | ||
| 118 | * \f$a=\frac{1}{2}\|\mathbf{r}\|^2\f$) | ||
| 119 | * | ||
| 120 | * @param[in] state State of the dynamical system | ||
| 121 | * @param[in] residual Residual model | ||
| 122 | */ | ||
| 123 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 124 | std::shared_ptr<ResidualModelAbstract> residual); | ||
| 125 | |||
| 126 | /** | ||
| 127 | * @copybrief CostModelAbstractTpl() | ||
| 128 | * | ||
| 129 | * We use `ActivationModelQuadTpl` as a default activation model (i.e., | ||
| 130 | * \f$a=\frac{1}{2}\|\mathbf{r}\|^2\f$) | ||
| 131 | * | ||
| 132 | * @param[in] state State of the system | ||
| 133 | * @param[in] nr Dimension of residual vector | ||
| 134 | * @param[in] nu Dimension of control vector | ||
| 135 | */ | ||
| 136 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 137 | const std::size_t nr, const std::size_t nu); | ||
| 138 | |||
| 139 | /** | ||
| 140 | * @copybrief CostModelAbstractTpl() | ||
| 141 | * | ||
| 142 | * We use `ActivationModelQuadTpl` as a default activation model (i.e., | ||
| 143 | * \f$a=\frac{1}{2}\|\mathbf{r}\|^2\f$). Furthermore, the default `nu` value | ||
| 144 | * is obtained from `StateAbstractTpl::get_nv()`. | ||
| 145 | * | ||
| 146 | * @param[in] state State of the dynamical system | ||
| 147 | * @param[in] nr Dimension of residual vector | ||
| 148 | * @param[in] nu Dimension of control vector | ||
| 149 | */ | ||
| 150 | CostModelAbstractTpl(std::shared_ptr<StateAbstract> state, | ||
| 151 | const std::size_t nr); | ||
| 152 | 15384 | virtual ~CostModelAbstractTpl() = default; | |
| 153 | |||
| 154 | /** | ||
| 155 | * @brief Compute the cost value and its residual vector | ||
| 156 | * | ||
| 157 | * @param[in] data Cost data | ||
| 158 | * @param[in] x State point \f$\mathbf{x}\in\mathbb{R}^{ndx}\f$ | ||
| 159 | * @param[in] u Control input \f$\mathbf{u}\in\mathbb{R}^{nu}\f$ | ||
| 160 | */ | ||
| 161 | virtual void calc(const std::shared_ptr<CostDataAbstract>& data, | ||
| 162 | const Eigen::Ref<const VectorXs>& x, | ||
| 163 | const Eigen::Ref<const VectorXs>& u) = 0; | ||
| 164 | |||
| 165 | /** | ||
| 166 | * @brief Compute the total cost value for nodes that depends only on the | ||
| 167 | * state | ||
| 168 | * | ||
| 169 | * It updates the total cost based on the state only. This function is used in | ||
| 170 | * the terminal nodes of an optimal control problem. | ||
| 171 | * | ||
| 172 | * @param[in] data Cost data | ||
| 173 | * @param[in] x State point \f$\mathbf{x}\in\mathbb{R}^{ndx}\f$ | ||
| 174 | */ | ||
| 175 | virtual void calc(const std::shared_ptr<CostDataAbstract>& data, | ||
| 176 | const Eigen::Ref<const VectorXs>& x); | ||
| 177 | |||
| 178 | /** | ||
| 179 | * @brief Compute the Jacobian and Hessian of cost and its residual vector | ||
| 180 | * | ||
| 181 | * It computes the Jacobian and Hessian of the cost function. It assumes that | ||
| 182 | * `calc()` has been run first. | ||
| 183 | * | ||
| 184 | * @param[in] data Cost data | ||
| 185 | * @param[in] x State point \f$\mathbf{x}\in\mathbb{R}^{ndx}\f$ | ||
| 186 | * @param[in] u Control input \f$\mathbf{u}\in\mathbb{R}^{nu}\f$ | ||
| 187 | */ | ||
| 188 | virtual void calcDiff(const std::shared_ptr<CostDataAbstract>& data, | ||
| 189 | const Eigen::Ref<const VectorXs>& x, | ||
| 190 | const Eigen::Ref<const VectorXs>& u) = 0; | ||
| 191 | |||
| 192 | /** | ||
| 193 | * @brief Compute the Jacobian and Hessian of the cost functions with respect | ||
| 194 | * to the state only | ||
| 195 | * | ||
| 196 | * It updates the Jacobian and Hessian of the cost function based on the state | ||
| 197 | * only. This function is used in the terminal nodes of an optimal control | ||
| 198 | * problem. | ||
| 199 | * | ||
| 200 | * @param[in] data Cost data | ||
| 201 | * @param[in] x State point \f$\mathbf{x}\in\mathbb{R}^{ndx}\f$ | ||
| 202 | */ | ||
| 203 | virtual void calcDiff(const std::shared_ptr<CostDataAbstract>& data, | ||
| 204 | const Eigen::Ref<const VectorXs>& x); | ||
| 205 | |||
| 206 | /** | ||
| 207 | * @brief Create the cost data | ||
| 208 | * | ||
| 209 | * The default data contains objects to store the values of the cost, residual | ||
| 210 | * vector and their derivatives (first and second order derivatives). However, | ||
| 211 | * it is possible to specialize this function if we need to create additional | ||
| 212 | * data, for instance, to avoid dynamic memory allocation. | ||
| 213 | * | ||
| 214 | * @param data Data collector | ||
| 215 | * @return the cost data | ||
| 216 | */ | ||
| 217 | virtual std::shared_ptr<CostDataAbstract> createData( | ||
| 218 | DataCollectorAbstract* const data); | ||
| 219 | |||
| 220 | /** | ||
| 221 | * @brief Return the state | ||
| 222 | */ | ||
| 223 | const std::shared_ptr<StateAbstract>& get_state() const; | ||
| 224 | |||
| 225 | /** | ||
| 226 | * @brief Return the activation model | ||
| 227 | */ | ||
| 228 | const std::shared_ptr<ActivationModelAbstract>& get_activation() const; | ||
| 229 | |||
| 230 | /** | ||
| 231 | * @brief Return the residual model | ||
| 232 | */ | ||
| 233 | const std::shared_ptr<ResidualModelAbstract>& get_residual() const; | ||
| 234 | |||
| 235 | /** | ||
| 236 | * @brief Return the dimension of the control input | ||
| 237 | */ | ||
| 238 | std::size_t get_nu() const; | ||
| 239 | |||
| 240 | /** | ||
| 241 | * @brief Print information on the cost model | ||
| 242 | */ | ||
| 243 | template <class Scalar> | ||
| 244 | friend std::ostream& operator<<(std::ostream& os, | ||
| 245 | const CostModelAbstractTpl<Scalar>& model); | ||
| 246 | |||
| 247 | /** | ||
| 248 | * @brief Modify the cost reference | ||
| 249 | */ | ||
| 250 | template <class ReferenceType> | ||
| 251 | void set_reference(ReferenceType ref); | ||
| 252 | |||
| 253 | /** | ||
| 254 | * @brief Return the cost reference | ||
| 255 | */ | ||
| 256 | template <class ReferenceType> | ||
| 257 | ReferenceType get_reference(); | ||
| 258 | |||
| 259 | /** | ||
| 260 | * @brief Print relevant information of the cost model | ||
| 261 | * | ||
| 262 | * @param[out] os Output stream object | ||
| 263 | */ | ||
| 264 | virtual void print(std::ostream& os) const; | ||
| 265 | |||
| 266 | protected: | ||
| 267 | /** | ||
| 268 | * @copybrief set_reference() | ||
| 269 | */ | ||
| 270 | virtual void set_referenceImpl(const std::type_info&, const void*); | ||
| 271 | |||
| 272 | /** | ||
| 273 | * @copybrief get_reference() | ||
| 274 | */ | ||
| 275 | virtual void get_referenceImpl(const std::type_info&, void*); | ||
| 276 | |||
| 277 | std::shared_ptr<StateAbstract> state_; //!< State description | ||
| 278 | std::shared_ptr<ActivationModelAbstract> activation_; //!< Activation model | ||
| 279 | std::shared_ptr<ResidualModelAbstract> residual_; //!< Residual model | ||
| 280 | std::size_t nu_; //!< Control dimension | ||
| 281 | VectorXs unone_; //!< No control vector | ||
| 282 | ✗ | CostModelAbstractTpl() | |
| 283 | ✗ | : state_(nullptr), activation_(nullptr), residual_(nullptr), nu_(0) {} | |
| 284 | }; | ||
| 285 | |||
| 286 | template <typename _Scalar> | ||
| 287 | struct CostDataAbstractTpl { | ||
| 288 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 289 | |||
| 290 | typedef _Scalar Scalar; | ||
| 291 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 292 | typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract; | ||
| 293 | typedef ResidualDataAbstractTpl<Scalar> ResidualDataAbstract; | ||
| 294 | typedef DataCollectorAbstractTpl<Scalar> DataCollectorAbstract; | ||
| 295 | typedef typename MathBase::VectorXs VectorXs; | ||
| 296 | typedef typename MathBase::MatrixXs MatrixXs; | ||
| 297 | |||
| 298 | template <template <typename Scalar> class Model> | ||
| 299 | 478159 | CostDataAbstractTpl(Model<Scalar>* const model, | |
| 300 | DataCollectorAbstract* const data) | ||
| 301 | 478159 | : shared(data), | |
| 302 | 478159 | activation(model->get_activation()->createData()), | |
| 303 |
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478159 | residual(model->get_residual()->createData(data)), |
| 304 | 478159 | cost(Scalar(0.)), | |
| 305 |
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478159 | Lx(model->get_state()->get_ndx()), |
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478159 | Lu(model->get_nu()), |
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478159 | Lxx(model->get_state()->get_ndx(), model->get_state()->get_ndx()), |
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478159 | Lxu(model->get_state()->get_ndx(), model->get_nu()), |
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956318 | Luu(model->get_nu(), model->get_nu()) { |
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478159 | Lx.setZero(); |
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478159 | Lu.setZero(); |
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478159 | Lxx.setZero(); |
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478159 | Lxu.setZero(); |
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478159 | Luu.setZero(); |
| 315 | 478159 | } | |
| 316 | 950814 | virtual ~CostDataAbstractTpl() = default; | |
| 317 | |||
| 318 | ✗ | DEPRECATED( | |
| 319 | "Use residual.r", const VectorXs& get_r() const { return residual->r; };) | ||
| 320 | ✗ | DEPRECATED( | |
| 321 | "Use residual.Rx", | ||
| 322 | const MatrixXs& get_Rx() const { return residual->Rx; };) | ||
| 323 | ✗ | DEPRECATED( | |
| 324 | "Use residual.Ru", | ||
| 325 | const MatrixXs& get_Ru() const { return residual->Ru; };) | ||
| 326 | ✗ | DEPRECATED( | |
| 327 | "Use residual.r", void set_r(const VectorXs& r) { residual->r = r; };) | ||
| 328 | ✗ | DEPRECATED( | |
| 329 | "Use residual.Rx", | ||
| 330 | void set_Rx(const MatrixXs& Rx) { residual->Rx = Rx; };) | ||
| 331 | ✗ | DEPRECATED( | |
| 332 | "Use residual.Ru", | ||
| 333 | void set_Ru(const MatrixXs& Ru) { residual->Ru = Ru; };) | ||
| 334 | |||
| 335 | DataCollectorAbstract* shared; | ||
| 336 | std::shared_ptr<ActivationDataAbstract> activation; | ||
| 337 | std::shared_ptr<ResidualDataAbstract> residual; | ||
| 338 | Scalar cost; | ||
| 339 | VectorXs Lx; | ||
| 340 | VectorXs Lu; | ||
| 341 | MatrixXs Lxx; | ||
| 342 | MatrixXs Lxu; | ||
| 343 | MatrixXs Luu; | ||
| 344 | }; | ||
| 345 | |||
| 346 | } // namespace crocoddyl | ||
| 347 | |||
| 348 | /* --- Details -------------------------------------------------------------- */ | ||
| 349 | /* --- Details -------------------------------------------------------------- */ | ||
| 350 | /* --- Details -------------------------------------------------------------- */ | ||
| 351 | #include "crocoddyl/core/cost-base.hxx" | ||
| 352 | |||
| 353 | CROCODDYL_DECLARE_EXTERN_TEMPLATE_CLASS(crocoddyl::CostModelAbstractTpl) | ||
| 354 | CROCODDYL_DECLARE_EXTERN_TEMPLATE_STRUCT(crocoddyl::CostDataAbstractTpl) | ||
| 355 | |||
| 356 | #endif // CROCODDYL_CORE_COST_BASE_HPP_ | ||
| 357 |