Here are the classes, structs, unions and interfaces with brief descriptions:

roboptim::detail::add_shared_ptr< CLIST >	Transform a types list into a types list of shared pointers
roboptim::BadGradient< T >	Exception thrown when a gradient check fail
roboptim::CachedFunction< T >	Store previous function computation
roboptim::visualization::gnuplot::Command	Gnuplot command
roboptim::ConstantFunction	Constant function
roboptim::DerivableParametrizedFunction< F >	Parametrized function with parameter derivative available
roboptim::derivativeSize< DifferentiableFunction >
roboptim::derivativeSize< Function >
roboptim::derivativeSize< NTimesDerivableFunction< N > >
roboptim::derivativeSize< TwiceDifferentiableFunction >
roboptim::DummySolver	Dummy solver which always fails
roboptim::DummySolverLastState	Dummy solver which always fails, but returns the last state of the solver
roboptim::EigenMatrixDense	Tag type for functions using Eigen dense matrices
roboptim::EigenMatrixSparse	Tag type for functions using Eigen sparse matrices
roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >	Precise finite difference gradient computation
roboptim::GenericDifferentiableFunction< T >	Define an abstract derivable function ( )
roboptim::GenericFiniteDifferenceGradient< T, FdgPolicy >	Compute automatically a gradient with finite differences
roboptim::GenericFunction< T >	Define an abstract mathematical function ( )
roboptim::GenericFunctionTraits< T >	GenericFunction traits
roboptim::GenericFunctionTraits< EigenMatrixDense >	Trait specializing GenericFunction for Eigen dense matrices
roboptim::GenericFunctionTraits< EigenMatrixSparse >	Trait specializing GenericFunction for Eigen sparse matrices
roboptim::GenericLinearFunction< T >	Define an abstract linear function
roboptim::GenericNumericLinearFunction< T >	Build a linear function from a vector and a matrix
roboptim::GenericQuadraticFunction< T >	Define an abstract quadratic function
roboptim::GenericSolver	Abstract interface satisfied by all solvers
roboptim::GenericTwiceDifferentiableFunction< T >	Define an abstract function which is derivable twice ( )
roboptim::visualization::Gnuplot	Gnuplot script
roboptim::IdentityFunction	Identity function
roboptim::detail::ltvector
roboptim::NoSolution	Tag a result if no solution has been found
roboptim::NTimesDerivableFunction< DerivabilityOrder >	Define a $\mathbb{R} \rightarrow \mathbb{R}^m$ function, derivable n times ( $n \geq 2$ )
roboptim::NTimesDerivableFunction< 2 >	Explicit specialization for the stop case of NTimesDerivable class
roboptim::NumericQuadraticFunction	Build a quadratic function from a matrix and a vector
roboptim::Parameter	Parameters type
roboptim::ParametrizedFunction< F >	Define an abstract parametrized mathematical function ( )
roboptim::detail::printConstraint< P >
roboptim::Problem< F, CLIST >
roboptim::Problem< F, boost::mpl::vector<> >
roboptim::Result	Represents the solution of an optimization problem
roboptim::ResultWithWarnings	Represents the solution of an optimization problem when errors occurred during the solving process
roboptim::finiteDifferenceGradientPolicies::Simple< T >	Fast finite difference gradient computation
roboptim::Solver< F, C >	Solver for a specific problem class
roboptim::SolverError	Base exception class for solving errors
roboptim::SolverFactory< T >	Define a solver factory that instanciate the plug-ins
roboptim::SolverWarning	Exception used for non-critical errors during optimization
roboptim::Split< T >
roboptim::SumOfC1Squares	Sum of the squares of differentiable functions