Class ompl::base::GoalLazySamples: The Python bindings for GoalLazySamples class are still broken. The OMPL C++ code creates a new thread from which you should be able to call a python Goal sampling function. Acquiring the right threads and locks and messing around with the Python Global Interpreter Lock (GIL) is very tricky. See ompl/py-bindings/generate_bindings.py for an initial attempt to make this work.
Member ompl::base::InformedSampler::heuristicSolnCost (const State *statePtr) const: With the future invention of a heuristic class, this should move.
Member ompl::base::PathLengthDirectInfSampler::heuristicSolnCost (const State *statePtr) const override: Use a heuristic function for the full solution cost defined in OptimizationObjective or some new Heuristic class once said function is defined.
Class ompl::control::LTLPlanner: cite papers
Member ompl::geometric::BFMT::plan (BiDirMotion *x_init, BiDirMotion *x_goal, BiDirMotion *&connection_point, const base::PlannerTerminationCondition &ptc): This precomputation is useful only if the same planner is used many times. otherwise is probably a waste of time. Do a real precomputation before calling solve().
Member ompl::geometric::FMT::solve (const base::PlannerTerminationCondition &ptc) override: Create a PRM-like connection strategy