10 #ifndef CROCODDYL_CORE_NUMDIFF_STATE_HPP_ 11 #define CROCODDYL_CORE_NUMDIFF_STATE_HPP_ 13 #include <boost/make_shared.hpp> 14 #include <boost/shared_ptr.hpp> 16 #include "crocoddyl/core/fwd.hpp" 17 #include "crocoddyl/core/state-base.hpp" 21 template <
typename _Scalar>
22 class StateNumDiffTpl :
public StateAbstractTpl<_Scalar> {
24 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
26 typedef _Scalar Scalar;
27 typedef MathBaseTpl<Scalar> MathBase;
28 typedef StateAbstractTpl<_Scalar> Base;
29 typedef typename MathBase::VectorXs VectorXs;
30 typedef typename MathBase::MatrixXs MatrixXs;
32 explicit StateNumDiffTpl(boost::shared_ptr<Base> state);
33 virtual ~StateNumDiffTpl();
35 virtual VectorXs
zero()
const;
36 virtual VectorXs
rand()
const;
37 virtual void diff(
const Eigen::Ref<const VectorXs>& x0,
const Eigen::Ref<const VectorXs>& x1,
38 Eigen::Ref<VectorXs> dxout)
const;
39 virtual void integrate(
const Eigen::Ref<const VectorXs>& x,
const Eigen::Ref<const VectorXs>& dx,
40 Eigen::Ref<VectorXs> xout)
const;
56 virtual void Jdiff(
const Eigen::Ref<const VectorXs>& x0,
const Eigen::Ref<const VectorXs>& x1,
57 Eigen::Ref<MatrixXs> Jfirst, Eigen::Ref<MatrixXs> Jsecond, Jcomponent firstsecond = both)
const;
73 virtual void Jintegrate(
const Eigen::Ref<const VectorXs>& x,
const Eigen::Ref<const VectorXs>& dx,
74 Eigen::Ref<MatrixXs> Jfirst, Eigen::Ref<MatrixXs> Jsecond,
75 const Jcomponent firstsecond = both,
const AssignmentOp op = setto)
const;
77 virtual void JintegrateTransport(
const Eigen::Ref<const VectorXs>& x,
const Eigen::Ref<const VectorXs>& dx,
78 Eigen::Ref<MatrixXs> Jin,
const Jcomponent firstsecond = both)
const;
80 const Scalar get_disturbance()
const;
81 void set_disturbance(
const Scalar disturbance);
88 boost::shared_ptr<Base> state_;
109 #include "crocoddyl/core/numdiff/state.hxx" 111 #endif // CROCODDYL_CORE_NUMDIFF_STATE_HPP_ 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.
VectorXs lb_
Lower state limits.
VectorXs ub_
Upper state limits.
bool has_limits_
Indicates whether any of the state limits is finite.
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: and ...
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: and .
virtual VectorXs zero() const
Generate a zero state.
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.
std::size_t nx_
State dimension.
std::size_t nv_
Velocity dimension.
virtual VectorXs rand() const
Generate a random state.
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 x + dx to x.
std::size_t ndx_
State rate dimension.
std::size_t nq_
Configuration dimension.