| Line |
Branch |
Exec |
Source |
| 1 |
|
|
/////////////////////////////////////////////////////////////////////////////// |
| 2 |
|
|
// BSD 3-Clause License |
| 3 |
|
|
// |
| 4 |
|
|
// Copyright (C) 2020-2025, LAAS-CNRS, Heriot-Watt University |
| 5 |
|
|
// Copyright note valid unless otherwise stated in individual files. |
| 6 |
|
|
// All rights reserved. |
| 7 |
|
|
/////////////////////////////////////////////////////////////////////////////// |
| 8 |
|
|
|
| 9 |
|
|
#ifndef CROCODDYL_CORE_ACTIVATIONS_SMOOTH_2NORM_HPP_ |
| 10 |
|
|
#define CROCODDYL_CORE_ACTIVATIONS_SMOOTH_2NORM_HPP_ |
| 11 |
|
|
|
| 12 |
|
|
#include "crocoddyl/core/activation-base.hpp" |
| 13 |
|
|
#include "crocoddyl/core/fwd.hpp" |
| 14 |
|
|
|
| 15 |
|
|
namespace crocoddyl { |
| 16 |
|
|
|
| 17 |
|
|
/** |
| 18 |
|
|
* @brief Smooth-2Norm activation |
| 19 |
|
|
* |
| 20 |
|
|
* This activation function describes a smooth representation of a 2-norm of a |
| 21 |
|
|
* residual vector, i.e. \f[ \begin{equation} \sqrt{\epsilon + sum^nr_{i=0} |
| 22 |
|
|
* \|r_i\|^2} \end{equation} \f] where \f$\epsilon\f$ defines the smoothing |
| 23 |
|
|
* factor, \f$r_i\f$ is the scalar residual for the \f$i\f$ constraints, |
| 24 |
|
|
* \f$nr\f$ is the dimension of the residual vector. |
| 25 |
|
|
* |
| 26 |
|
|
* The computation of the function and it derivatives are carried out in |
| 27 |
|
|
* `calc()` and `caldDiff()`, respectively. |
| 28 |
|
|
* |
| 29 |
|
|
* \sa `calc()`, `calcDiff()`, `createData()` |
| 30 |
|
|
*/ |
| 31 |
|
|
template <typename _Scalar> |
| 32 |
|
|
class ActivationModelSmooth2NormTpl |
| 33 |
|
|
: public ActivationModelAbstractTpl<_Scalar> { |
| 34 |
|
|
public: |
| 35 |
|
|
EIGEN_MAKE_ALIGNED_OPERATOR_NEW |
| 36 |
|
✗ |
CROCODDYL_DERIVED_CAST(ActivationModelBase, ActivationModelSmooth2NormTpl) |
| 37 |
|
|
|
| 38 |
|
|
typedef _Scalar Scalar; |
| 39 |
|
|
typedef MathBaseTpl<Scalar> MathBase; |
| 40 |
|
|
typedef ActivationModelAbstractTpl<Scalar> Base; |
| 41 |
|
|
typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract; |
| 42 |
|
|
typedef typename MathBase::VectorXs VectorXs; |
| 43 |
|
|
typedef typename MathBase::MatrixXs MatrixXs; |
| 44 |
|
|
|
| 45 |
|
|
/** |
| 46 |
|
|
* @brief Initialize the smooth-2Norm activation model |
| 47 |
|
|
* |
| 48 |
|
|
* The default `eps` value is defined as 1. |
| 49 |
|
|
* |
| 50 |
|
|
* @param[in] nr Dimension of the residual vector |
| 51 |
|
|
* @param[in] eps Smoothing factor (default: 1.) |
| 52 |
|
|
*/ |
| 53 |
|
✗ |
explicit ActivationModelSmooth2NormTpl(const std::size_t nr, |
| 54 |
|
|
const Scalar eps = Scalar(1.)) |
| 55 |
|
✗ |
: Base(nr), eps_(eps) { |
| 56 |
|
✗ |
if (eps < Scalar(0.)) { |
| 57 |
|
✗ |
throw_pretty("Invalid argument: " << "eps should be a positive value"); |
| 58 |
|
|
} |
| 59 |
|
✗ |
}; |
| 60 |
|
✗ |
virtual ~ActivationModelSmooth2NormTpl() = default; |
| 61 |
|
|
|
| 62 |
|
|
/** |
| 63 |
|
|
* @brief Compute the smooth-2Norm function |
| 64 |
|
|
* |
| 65 |
|
|
* @param[in] data Smooth-2Norm activation data |
| 66 |
|
|
* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ |
| 67 |
|
|
*/ |
| 68 |
|
✗ |
virtual void calc(const std::shared_ptr<ActivationDataAbstract>& data, |
| 69 |
|
|
const Eigen::Ref<const VectorXs>& r) override { |
| 70 |
|
✗ |
if (static_cast<std::size_t>(r.size()) != nr_) { |
| 71 |
|
✗ |
throw_pretty( |
| 72 |
|
|
"Invalid argument: " << "r has wrong dimension (it should be " + |
| 73 |
|
|
std::to_string(nr_) + ")"); |
| 74 |
|
|
} |
| 75 |
|
|
using std::sqrt; |
| 76 |
|
✗ |
data->a_value = sqrt(r.squaredNorm() + eps_); |
| 77 |
|
✗ |
}; |
| 78 |
|
|
|
| 79 |
|
|
/** |
| 80 |
|
|
* @brief Compute the derivatives of the smooth-2Norm function |
| 81 |
|
|
* |
| 82 |
|
|
* @param[in] data Smooth-2Norm activation data |
| 83 |
|
|
* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ |
| 84 |
|
|
*/ |
| 85 |
|
✗ |
virtual void calcDiff(const std::shared_ptr<ActivationDataAbstract>& data, |
| 86 |
|
|
const Eigen::Ref<const VectorXs>& r) override { |
| 87 |
|
✗ |
if (static_cast<std::size_t>(r.size()) != nr_) { |
| 88 |
|
✗ |
throw_pretty( |
| 89 |
|
|
"Invalid argument: " << "r has wrong dimension (it should be " + |
| 90 |
|
|
std::to_string(nr_) + ")"); |
| 91 |
|
|
} |
| 92 |
|
|
|
| 93 |
|
✗ |
data->Ar = r / data->a_value; |
| 94 |
|
✗ |
data->Arr.diagonal().array() = Scalar(1) / pow(data->a_value, Scalar(3)); |
| 95 |
|
✗ |
}; |
| 96 |
|
|
|
| 97 |
|
|
/** |
| 98 |
|
|
* @brief Create the smooth-2norm activation data |
| 99 |
|
|
* |
| 100 |
|
|
* @return the activation data |
| 101 |
|
|
*/ |
| 102 |
|
✗ |
virtual std::shared_ptr<ActivationDataAbstract> createData() override { |
| 103 |
|
|
return std::allocate_shared<ActivationDataAbstract>( |
| 104 |
|
✗ |
Eigen::aligned_allocator<ActivationDataAbstract>(), this); |
| 105 |
|
|
}; |
| 106 |
|
|
|
| 107 |
|
|
template <typename NewScalar> |
| 108 |
|
✗ |
ActivationModelSmooth2NormTpl<NewScalar> cast() const { |
| 109 |
|
|
typedef ActivationModelSmooth2NormTpl<NewScalar> ReturnType; |
| 110 |
|
✗ |
ReturnType res(nr_, scalar_cast<NewScalar>(eps_)); |
| 111 |
|
✗ |
return res; |
| 112 |
|
|
} |
| 113 |
|
|
|
| 114 |
|
|
protected: |
| 115 |
|
|
/** |
| 116 |
|
|
* @brief Print relevant information of the smooth-1norm model |
| 117 |
|
|
* |
| 118 |
|
|
* @param[out] os Output stream object |
| 119 |
|
|
*/ |
| 120 |
|
✗ |
virtual void print(std::ostream& os) const override { |
| 121 |
|
✗ |
os << "ActivationModelSmooth2Norm {nr=" << nr_ << ", eps=" << eps_ << "}"; |
| 122 |
|
|
} |
| 123 |
|
|
|
| 124 |
|
|
using Base::nr_; //!< Dimension of the residual vector |
| 125 |
|
|
Scalar eps_; //!< Smoothing factor |
| 126 |
|
|
}; |
| 127 |
|
|
|
| 128 |
|
|
} // namespace crocoddyl |
| 129 |
|
|
|
| 130 |
|
|
CROCODDYL_DECLARE_EXTERN_TEMPLATE_CLASS( |
| 131 |
|
|
crocoddyl::ActivationModelSmooth2NormTpl) |
| 132 |
|
|
|
| 133 |
|
|
#endif // CROCODDYL_CORE_ACTIVATIONS_SMOOTH_2NORM_HPP_ |
| 134 |
|
|
|