ompl::geometric::CForest Class Reference
Coupled Forest of Random Engrafting Search Trees. More...
#include <ompl/geometric/planners/cforest/CForest.h>
Inheritance diagram for ompl::geometric::CForest:

Public Member Functions | |
CForest (const base::SpaceInformationPtr &si) | |
virtual void | getPlannerData (base::PlannerData &data) const |
Get information about the current run of the motion planner. Repeated calls to this function will update data (only additions are made). This is useful to see what changed in the exploration datastructure, between calls to solve(), for example (without calling clear() in between). | |
virtual void | clear () |
Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work. | |
template<class T > | |
void | addPlannerInstance () |
Add an specific planner instance. | |
template<class T > | |
void | addPlannerInstances (std::size_t num=2) |
Add an specific planner instance. | |
void | clearPlannerInstances () |
Remove all planner instances. | |
base::PlannerPtr & | getPlannerInstance (const std::size_t idx) |
Return an specific planner instance. | |
virtual void | setup () |
Perform extra configuration steps, if needed. This call will also issue a call to ompl::base::SpaceInformation::setup() if needed. This must be called before solving. | |
virtual base::PlannerStatus | solve (const base::PlannerTerminationCondition &ptc) |
Function that can solve the motion planning problem. This function can be called multiple times on the same problem, without calling clear() in between. This allows the planner to continue work for more time on an unsolved problem, for example. If this option is used, it is assumed the problem definition is not changed (unpredictable results otherwise). The only change in the problem definition that is accounted for is the addition of starting or goal states (but not changing previously added start/goal states). The function terminates if the call to ptc returns true. | |
void | addSampler (base::StateSamplerPtr sampler) |
void | setPrune (const bool prune) |
Option to control whether the tree is pruned during the search. | |
bool | getPrune () const |
Get the state of the pruning option. | |
void | setNumThreads (unsigned int numThreads=0) |
Set default number of threads to use when no planner instances are specified by the user. | |
unsigned int | getNumThreads () |
Get default number of threads used by CForest when no planner instances are specified by the user. | |
std::string | getBestCost () const |
Get best cost among all the planners. | |
std::string | getNumPathsShared () const |
Get number of paths shared by the algorithm. | |
std::string | getNumStatesShared () const |
Get number of states actually shared by the algorithm. | |
Protected Member Functions | |
void | solve (base::Planner *planner, const base::PlannerTerminationCondition &ptc) |
Manages the call to solve() for each individual planner. | |
Protected Attributes | |
base::OptimizationObjectivePtr | opt_ |
Optimization objective taken into account when planning. | |
std::vector< base::PlannerPtr > | planners_ |
The set of planners to be used. | |
std::vector < base::StateSamplerPtr > | samplers_ |
The set of sampler allocated by the planners. | |
boost::unordered_set< const base::State * > | statesShared_ |
Stores the states already shared to check if a specific state has been shared. | |
base::Cost | bestCost_ |
Cost of the best path found so far among planners. | |
unsigned int | numPathsShared_ |
Number of paths shared among threads. | |
unsigned int | numStatesShared_ |
Number of states shared among threads. | |
boost::mutex | newSolutionFoundMutex_ |
Mutex to control the access to the newSolutionFound() method. | |
boost::mutex | addSamplerMutex_ |
Mutex to control the access to samplers_. | |
bool | prune_ |
Flag to control the tree pruning. | |
unsigned int | numThreads_ |
Default number of threads to use when no planner instances are specified by the user. |
Detailed Description
Coupled Forest of Random Engrafting Search Trees.
- Short description
- CForest (Coupled Forest of Random Engrafting Search Trees) is a parallelization framework that is designed for single-query shortest path planning algorithms. It is not a planning algorithm per se.
CForest is designed to be used with any random tree algorithm that operates in any configuration space such that: 1) the search tree has almost sure convergence to the optimal solution and 2) the configuration space obeys the triangle inequality. It relies in the OptimizationObjective set for the underlying planners.
See also the extensive documentation [here](CForest.html).
- External documentation
- M. Otte, N. Correll, C-FOREST: Parallel Shortest Path Planning With Superlinear Speedup, IEEE Transactions on Robotics, Vol 20, No 3, 2013. DOI: [10.1109/TRO.2013.2240176](http://dx.doi.org/10.1109/TRO.2013.2240176)
[[PDF]](http://ieeexplore.ieee.org/ielx5/8860/6522877/06425493.pdf?tp=&arnumber=6425493&isnumber=6522877)
The documentation for this class was generated from the following files:
- ompl/geometric/planners/cforest/CForest.h
- ompl/geometric/planners/cforest/src/CForest.cpp