Crocoddyl
 
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state.hpp
1
2// BSD 3-Clause License
3//
4// Copyright (C) 2019-2023, LAAS-CNRS, New York University, Max Planck
5// Gesellschaft,
6// University of Edinburgh, Heriot-Watt University
7// Copyright note valid unless otherwise stated in individual files.
8// All rights reserved.
10
11#ifndef CROCODDYL_CORE_NUMDIFF_STATE_HPP_
12#define CROCODDYL_CORE_NUMDIFF_STATE_HPP_
13
14#include <boost/make_shared.hpp>
15#include <memory>
16
17#include "crocoddyl/core/fwd.hpp"
18#include "crocoddyl/core/state-base.hpp"
19
20namespace crocoddyl {
21
22template <typename _Scalar>
23class StateNumDiffTpl : public StateAbstractTpl<_Scalar> {
24 public:
25 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
26
27 typedef _Scalar Scalar;
30 typedef typename MathBase::VectorXs VectorXs;
31 typedef typename MathBase::MatrixXs MatrixXs;
32
33 explicit StateNumDiffTpl(std::shared_ptr<Base> state);
34 virtual ~StateNumDiffTpl();
35
36 virtual VectorXs zero() const;
37 virtual VectorXs rand() const;
38 virtual void diff(const Eigen::Ref<const VectorXs>& x0,
39 const Eigen::Ref<const VectorXs>& x1,
40 Eigen::Ref<VectorXs> dxout) const;
41 virtual void integrate(const Eigen::Ref<const VectorXs>& x,
42 const Eigen::Ref<const VectorXs>& dx,
43 Eigen::Ref<VectorXs> xout) const;
59 virtual void Jdiff(const Eigen::Ref<const VectorXs>& x0,
60 const Eigen::Ref<const VectorXs>& x1,
61 Eigen::Ref<MatrixXs> Jfirst, Eigen::Ref<MatrixXs> Jsecond,
62 Jcomponent firstsecond = both) const;
78 virtual void Jintegrate(const Eigen::Ref<const VectorXs>& x,
79 const Eigen::Ref<const VectorXs>& dx,
80 Eigen::Ref<MatrixXs> Jfirst,
81 Eigen::Ref<MatrixXs> Jsecond,
82 const Jcomponent firstsecond = both,
83 const AssignmentOp op = setto) const;
84
85 virtual void JintegrateTransport(const Eigen::Ref<const VectorXs>& x,
86 const Eigen::Ref<const VectorXs>& dx,
87 Eigen::Ref<MatrixXs> Jin,
88 const Jcomponent firstsecond = both) const;
89
94 const Scalar get_disturbance() const;
95
100 void set_disturbance(const Scalar disturbance);
101
102 private:
103 std::shared_ptr<Base>
104 state_;
105 Scalar e_jac_;
107
108 protected:
109 using Base::has_limits_;
110 using Base::lb_;
111 using Base::ndx_;
112 using Base::nq_;
113 using Base::nv_;
114 using Base::nx_;
115 using Base::ub_;
116};
117
118} // namespace crocoddyl
119
120/* --- Details -------------------------------------------------------------- */
121/* --- Details -------------------------------------------------------------- */
122/* --- Details -------------------------------------------------------------- */
123#include "crocoddyl/core/numdiff/state.hxx"
124
125#endif // CROCODDYL_CORE_NUMDIFF_STATE_HPP_
Abstract class for the state representation.
std::size_t nv_
Velocity dimension.
std::size_t nx_
State dimension.
bool has_limits_
Indicates whether any of the state limits is finite.
std::size_t nq_
Configuration dimension.
VectorXs lb_
Lower state limits.
VectorXs ub_
Upper state limits.
std::size_t ndx_
State rate dimension.
virtual void integrate(const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &dx, Eigen::Ref< VectorXs > xout) const
Compute the state manifold integration.
virtual VectorXs zero() const
Generate a zero state.
virtual void Jdiff(const Eigen::Ref< const VectorXs > &x0, const Eigen::Ref< const VectorXs > &x1, Eigen::Ref< MatrixXs > Jfirst, Eigen::Ref< MatrixXs > Jsecond, Jcomponent firstsecond=both) const
This computes the Jacobian of the diff method by finite differentiation:
const Scalar get_disturbance() const
Return the disturbance constant used in the numerical differentiation routine.
virtual void diff(const Eigen::Ref< const VectorXs > &x0, const Eigen::Ref< const VectorXs > &x1, Eigen::Ref< VectorXs > dxout) const
Compute the state manifold differentiation.
void set_disturbance(const Scalar disturbance)
Modify the disturbance constant used by the numerical differentiation routine.
virtual void JintegrateTransport(const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &dx, Eigen::Ref< MatrixXs > Jin, const Jcomponent firstsecond=both) const
Parallel transport from integrate(x, dx) to x.
virtual void Jintegrate(const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &dx, Eigen::Ref< MatrixXs > Jfirst, Eigen::Ref< MatrixXs > Jsecond, const Jcomponent firstsecond=both, const AssignmentOp op=setto) const
This computes the Jacobian of the integrate method by finite differentiation:
virtual VectorXs rand() const
Generate a random state.