|
| | DifferentialActionModelAbstractTpl (boost::shared_ptr< StateAbstract > state, const std::size_t nu, const std::size_t nr=0) |
| | Initialize the differential action model. More...
|
| |
| virtual void | calc (const boost::shared_ptr< DifferentialActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x) |
| | Compute the total cost value for nodes that depends only on the state. More...
|
| |
| virtual void | calc (const boost::shared_ptr< DifferentialActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0 |
| | Compute the system acceleration and cost value. More...
|
| |
| virtual void | calcDiff (const boost::shared_ptr< DifferentialActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x) |
| | Compute the derivatives of the cost functions with respect to the state only. More...
|
| |
| virtual void | calcDiff (const boost::shared_ptr< DifferentialActionDataAbstract > &data, const Eigen::Ref< const VectorXs > &x, const Eigen::Ref< const VectorXs > &u)=0 |
| | Compute the derivatives of the dynamics and cost functions. More...
|
| |
|
virtual bool | checkData (const boost::shared_ptr< DifferentialActionDataAbstract > &data) |
| | Checks that a specific data belongs to this model.
|
| |
| virtual boost::shared_ptr< DifferentialActionDataAbstract > | createData () |
| | Create the differential action data. More...
|
| |
|
bool | get_has_control_limits () const |
| | Indicates if there are defined control limits.
|
| |
|
std::size_t | get_nr () const |
| | Return the dimension of the cost-residual vector.
|
| |
|
std::size_t | get_nu () const |
| | Return the dimension of the control input.
|
| |
|
const boost::shared_ptr< StateAbstract > & | get_state () const |
| | Return the state.
|
| |
|
const VectorXs & | get_u_lb () const |
| | Return the control lower bound.
|
| |
|
const VectorXs & | get_u_ub () const |
| | Return the control upper bound.
|
| |
| virtual void | print (std::ostream &os) const |
| | Print relevant information of the differential action model. More...
|
| |
| virtual void | quasiStatic (const boost::shared_ptr< DifferentialActionDataAbstract > &data, Eigen::Ref< VectorXs > u, const Eigen::Ref< const VectorXs > &x, const std::size_t maxiter=100, const Scalar tol=Scalar(1e-9)) |
| | Computes the quasic static commands. More...
|
| |
| VectorXs | quasiStatic_x (const boost::shared_ptr< DifferentialActionDataAbstract > &data, const VectorXs &x, const std::size_t maxiter=100, const Scalar tol=Scalar(1e-9)) |
| |
|
void | set_u_lb (const VectorXs &u_lb) |
| | Modify the control lower bounds.
|
| |
|
void | set_u_ub (const VectorXs &u_ub) |
| | Modify the control upper bounds.
|
| |
template<typename _Scalar>
class crocoddyl::DifferentialActionModelAbstractTpl< _Scalar >
Abstract class for differential action model.
A differential action model is the time-continuous version of an action model, i.e.
\[ \begin{aligned} &\dot{\mathbf{v}} = \mathbf{f}(\mathbf{q}, \mathbf{v}, \mathbf{u}), &\textrm{(dynamics)}\\ &l(\mathbf{x},\mathbf{u}) = \int_0^{\delta t} a(\mathbf{r}(\mathbf{x},\mathbf{u}))\,dt, &\textrm{(cost)} \end{aligned} \]
where the configuration \(\mathbf{q}\in\mathcal{Q}\) lies in the configuration manifold described with a nq-tuple, the velocity \(\mathbf{v}\in T_{\mathbf{q}}\mathcal{Q}\) its a tangent vector to this manifold with nv dimension, \(\mathbf{u}\in\mathbb{R}^{nu}\) is the input commands, \(\mathbf{r}\) and \(a\) is a residual and activation functions (see ActivationModelAbstractTpl). Both configuration and velocity describe the system space \(\mathbf{x}\in\mathbf{X}\) which lies in the state manifold. Note that the acceleration \(\dot{\mathbf{v}}\in T_{\mathbf{q}}\mathcal{Q}\) lies also in the tangent space of the configuration manifold.
The main computations are carrying out in calc and calcDiff. calc computes the acceleration and cost and calcDiff computes the derivatives of the dynamics and cost function. Concretely speaking, calcDiff builds a linear-quadratic approximation of the differential action, where the dynamics and cost functions have linear and quadratic forms, respectively. \(\mathbf{f_x}\in\mathbb{R}^{nv\times ndx}\), \(\mathbf{f_u}\in\mathbb{R}^{nv\times nu}\) are the Jacobians of the dynamics; \(\mathbf{l_x}\in\mathbb{R}^{ndx}\), \(\mathbf{l_u}\in\mathbb{R}^{nu}\), \(\mathbf{l_{xx}}\in\mathbb{R}^{ndx\times ndx}\), \(\mathbf{l_{xu}}\in\mathbb{R}^{ndx\times nu}\), \(\mathbf{l_{uu}}\in\mathbb{R}^{nu\times nu}\) are the Jacobians and Hessians of the cost function, respectively. Additionally, it is important remark that calcDiff() computes the derivates using the latest stored values by calc(). Thus, we need to run first calc().
- See also
calc(), calcDiff(), createData()
Definition at line 53 of file diff-action-base.hpp.
1.8.17