aligator  0.14.0
A primal-dual augmented Lagrangian-type solver for nonlinear trajectory optimization.
Loading...
Searching...
No Matches
Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234]
 Caligator::gar::LqrKnotTpl< Scalar >::__view_base< IsConst >
 C_FunType
 Caligator::SolverProxDDPTpl< _Scalar >::AlmParams
 CBase
 CBaseData
 Caligator::BlkMatrix< _MatrixType, _N, _M >Block matrix class, with a fixed-size number of row and column blocks
 Caligator::python::BlkMatrixPythonVisitor< BlockMatrixType >
 Caligator::CallbackBaseTpl< Scalar >Base callback class
 Caligator::vector< T >::const_iteratorSTL iterator class
 Caligator::vector< T >::const_reverse_iteratorSTL iterator class
 Caligator::ConstraintProximalScalerTpl< Scalar >
 Caligator::ConstraintSetTpl< _Scalar >Base constraint set type
 Caligator::ConstraintSetTpl< Scalar >
 Caligator::ConstraintStackTpl< Scalar >Convenience class to manage a stack of constraints
 Caligator::ContactMapTpl< _Scalar >Contact map for centroidal costs and dynamics
 Caligator::dynamics::ContinuousDynamicsAbstractTpl< _Scalar >Continuous dynamics described by differential-algebraic equations (DAEs) \(F(\dot{x}, x, u) = 0\)
 Caligator::dynamics::ContinuousDynamicsAbstractTpl< Scalar >
 Caligator::dynamics::ContinuousDynamicsDataTpl< _Scalar >Data struct for ContinuousDynamicsAbstractTpl
 Caligator::dynamics::ContinuousDynamicsDataTpl< Scalar >
 Caligator::context::CostAbstractTpl< _Scalar >Stage costs \( \ell(x, u) \) for control problems
 Caligator::CostAbstractTpl< _Scalar >Stage costs \( \ell(x, u) \) for control problems
 Caligator::CostAbstractTpl< Scalar >
 Caligator::CostDataAbstractTpl< _Scalar >Data struct for CostAbstractTpl
 Caligator::CostDataAbstractTpl< Scalar >
 Caligator::DirectSumCostTpl< _Scalar >::Data
 Caligator::DirectSumExplicitDynamicsTpl< _Scalar >::Data
 Caligator::gar::DenseKernel< _Scalar >::Data
 Cbp::def_visitor
 Caligator::gar::DenseKernel< _Scalar >A dense Bunch-Kaufman based kernel
 Caligator::DynamicsDataTpl< _Scalar >
 Caligator::DynamicsDataTpl< Scalar >
 Caligator::DynamicsModelTpl< _Scalar >Dynamics model: describes system dynamics through an implicit relation \(f(x,u,x') = 0\)
 Caligator::DynamicsModelTpl< Scalar >
 Cxyz::detail::empty_base_optimization< T, CanBeEmptyBaseClass >
 Cxyz::detail::empty_base_optimization< A >
 Cdetail::empty_base_optimization< std::allocator< aligator::ConstraintSetTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::CostAbstractTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::dynamics::ContinuousDynamicsAbstractTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::dynamics::ODEAbstractTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::ExplicitDynamicsModelTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::ManifoldAbstractTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::StageFunctionTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< aligator::UnaryFunctionTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< ConstraintSetTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< ManifoldAbstractTpl< Scalar > > >
 Cdetail::empty_base_optimization< std::allocator< StageFunctionTpl< Scalar > > >
 CMyLibrary::ExampleExample class to demonstrate the features of the custom CSS
 Cstd::exceptionSTL class
 Caligator::FilterTpl< Scalar >A basic filter line-search strategy
 Caligator::forwardDynamics< T >Evaluates the forward map for a discrete dynamics model, implicit or explicit
 Caligator::frame_api
 Caligator::Linesearch< T >::FunctionSample
 Caligator::FunctionSliceXprTpl< Scalar, Base >Represents a function of which the output is a subset of another function, for instance \(x \mapsto f_\{0, 1, 3\}(x) \) where \(f\) is given
 Cxyz::in_place_type_t< T >
 Cboost::python::instance_holder
 Caligator::vector< T >::iteratorSTL iterator class
 Caligator::gar::ProximalRiccatiKernel< Scalar >::kkt0_t
 Caligator::LagrangianDerivatives< Scalar >Compute the derivatives of the problem Lagrangian
 Caligator::Linesearch< T >Base linesearch class. Design pattern inspired by Google Ceres-Solver
 Caligator::Linesearch< Scalar >
 Caligator::SolverProxDDPTpl< _Scalar >::LinesearchVariant
 Caligator::LogColumn
 Caligator::LoggerA table logging utility to log the trace of the numerical solvers
 Caligator::gar::LqrKnotTpl< Scalar >Struct describing a stage of a constrained LQ problem
 Caligator::gar::LqrProblemTpl< Scalar >
 Caligator::ManagedMatrix< _Scalar, _Rows, _Cols, _Options, Alignment >Thin wrapper around Eigen::Map representing a matrix object with memory managed by a C++17 polymorphic allocator
 Caligator::ManifoldAbstractTpl< _Scalar >Base class for manifolds, to use in cost funcs, solvers..
 Caligator::ManifoldAbstractTpl< _LieGroup::Scalar >
 Caligator::ManifoldAbstractTpl< Base::Scalar >
 Caligator::ManifoldAbstractTpl< MultibodyConfiguration< Scalar >::Scalar >
 Caligator::ManifoldAbstractTpl< Scalar >
 Caligator::math_types< _Scalar >Typedefs for math (Eigen vectors, matrices) depending on scalar type
 Caligator::NewtonRaphson< Scalar >Newton-Raphson procedure, e.g. to compute forward dynamics from implicit functions
 Caligator::no_alloc_tTag type for e.g. non-allocating constructors
 Caligator::Linesearch< T >::Options
 Caligator::NewtonRaphson< Scalar >::Options
 Caligator::PDALFunction< _Scalar >Primal-dual augmented Lagrangian merit function
 Cstd::pmr::polymorphic_allocator
 Caligator::python::PolymorphicVisitor< Poly >
 Caligator::PolynomialTpl< T >Polynomials represented by their coefficients in decreasing order of degree
 Caligator::gar::ProximalRiccatiKernel< Scalar >Kernel for use in Riccati-like algorithms for the proximal LQ subproblem
 Caligator::QFunctionTpl< _Scalar >Q-function model parameters
 Caligator::ResultsBaseTpl< _Scalar >
 Caligator::ResultsBaseTpl< Scalar >
 Caligator::vector< T >::reverse_iteratorSTL iterator class
 Caligator::gar::RiccatiSolverBase< _Scalar >
 Caligator::gar::RiccatiSolverBase< Scalar >
 CMyLibrary::SecondExample
 Caligator::shared_ptr< T >STL class
 Caligator::detail::slice_impl_tpl< Base >Slicing and indexing of a function's output
 Caligator::detail::slice_impl_tpl< StageFunctionTpl< Scalar > >
 Caligator::detail::slice_impl_tpl< UnaryFunctionTpl< Scalar > >
 CSolverBase
 Caligator::SolverFDDPTpl< Scalar >The feasible DDP (FDDP) algorithm, from Mastalli et al. (2020)
 Caligator::SolverProxDDPTpl< _Scalar >A proximal, augmented Lagrangian-type solver for trajectory optimization
 Caligator::StageConstraintTpl< Scalar >Simple struct holding together a function and set, to describe a constraint
 Caligator::StageDataTpl< _Scalar >Data struct for stage models StageModelTpl
 Caligator::StageDataTpl< Scalar >
 Caligator::gar::StageFactor< _Scalar >Per-node struct for all computations in the factorization
 Caligator::StageFunctionDataTpl< _Scalar >Base struct for function data
 Caligator::StageFunctionDataTpl< Scalar >
 Caligator::StageFunctionTpl< _Scalar >Class representing ternary functions \(f(x,u,x')\)
 Caligator::StageFunctionTpl< Scalar >
 Caligator::StageModelTpl< _Scalar >A stage in the control problem
 Caligator::StageModelTpl< Scalar >
 CT
 Caligator::TrajOptDataTpl< _Scalar >Problem data struct
 Caligator::TrajOptProblemTpl< _Scalar >Trajectory optimization problem
 CTs...
 Caligator::gar::DenseKernel< _Scalar >::value
 Caligator::gar::StageFactor< _Scalar >::value_t
 Caligator::ValueFunctionTpl< _Scalar >Storage for the value function model parameters
 Caligator::vector< T >STL class
 Caligator::gar::workrange_t
 Caligator::WorkspaceBaseTpl< Scalar >Base workspace struct for the algorithms
 Cboost::python::wrapper