#include <rrt.h>
Inheritance diagram for RRT::
Public Methods  
RRT (Problem *problem)  
A constructor that initializes data members.  
virtual  ~RRT () 
Empty destructor.  
virtual void  Reset () 
Reset the planner.  
virtual bool  Plan () 
Attempt to solve an InitialGoal query by growing an RRT.  
Public Attributes  
bool  UseANN 
If true, then the ANN package is used for nearest neighbors. It assumes R^n topology and Euclidean metric. The default is false.  
double  GoalDist 
The distance of the closest RRT MSLNode to the goal.  
MSLVector  BestState 
The closest state to the goal so far (not used in dualtree planners).  
double  ConnectTimeLimit 
The maximum amount of time to move in a Connect step (default = INFINITY).  
int  SatisfiedCount 
Number of times the collision checker has been called.  
Protected Methods  
virtual MSLVector  SelectInput (const MSLVector &x1, const MSLVector &x2, MSLVector &nx_best, bool &success, bool forward) 
Select the input that gets closest to x2 from x1.  
virtual MSLNode*  SelectNode (const MSLVector &x, MSLTree *t, bool forward) 
Return the nearest neighbor in the graph.  
virtual bool  Extend (const MSLVector &x, MSLTree *t, MSLNode *&nn, bool forward) 
Incrementally extend the RRT.  
virtual bool  Connect (const MSLVector &x, MSLTree *t, MSLNode *&nn, bool forward) 
Iterated Extend.  
virtual MSLVector  ChooseState () 
Pick a state using some sampling technique. 
The base class for the planners based on Rapidlyexploring Random Trees. In the base class, a single tree is generated without any regard to the GoalState. The best planners to try are RRTGoalBias and RRTGoalZoom for single trees, and RRTConCon and RRTExtExt for dual trees. Dual tree approaches are much more efficient than single tree approaches, assuming dual trees can be applied.

A constructor that initializes data members.


Empty destructor.


Pick a state using some sampling technique.
Reimplemented in RRTGoalBias, RRTGoalZoom, RRTPolar, and RRTHull. 

Iterated Extend.
Reimplemented in RRTSlide. 

Incrementally extend the RRT.


Attempt to solve an InitialGoal query by growing an RRT.
Reimplemented from Planner. Reimplemented in RRTCon, RRTDual, RRTExtExt, RRTExtCon, and RRTConCon. 

Reset the planner.
Reimplemented from Planner. 

Select the input that gets closest to x2 from x1.
Reimplemented in RandomTree, and RRTSlide. 

Return the nearest neighbor in the graph.
Reimplemented in RandomTree. 

The closest state to the goal so far (not used in dualtree planners).


The maximum amount of time to move in a Connect step (default = INFINITY).


The distance of the closest RRT MSLNode to the goal.


Number of times the collision checker has been called.


If true, then the ANN package is used for nearest neighbors. It assumes R^n topology and Euclidean metric. The default is false.
