ompl::geometric::PDST Class Reference
Path-Directed Subdivision Tree. More...
#include <ompl/geometric/planners/pdst/PDST.h>
Inheritance diagram for ompl::geometric::PDST:

Classes | |
struct | Cell |
Cell is a Binary Space Partition. More... | |
struct | Motion |
Class representing the tree of motions exploring the state space. More... | |
struct | MotionCompare |
Comparator used to order motions in the priority queue. More... | |
Public Member Functions | |
PDST (const base::SpaceInformationPtr &si) | |
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. | |
virtual void | clear () |
Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work. | |
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 void | getPlannerData (base::PlannerData &data) const |
Extracts the planner data from the priority queue into data. | |
void | setProjectionEvaluator (const base::ProjectionEvaluatorPtr &projectionEvaluator) |
Set the projection evaluator. This class is able to compute the projection of a given state. | |
void | setProjectionEvaluator (const std::string &name) |
Set the projection evaluator (select one from the ones registered with the state space). | |
const base::ProjectionEvaluatorPtr & | getProjectionEvaluator () const |
Get the projection evaluator. | |
*void | setGoalBias (double goalBias) |
In the process of randomly selecting states in the state space to attempt to go towards, the algorithm may in fact choose the actual goal state, if it knows it, with some probability. This probability is a real number between 0.0 and 1.0; its value should usually be around 0.05 and should not be too large. It is probably a good idea to use the default value. | |
double | getGoalBias () const |
Get the goal bias the planner is using */. | |
Protected Member Functions | |
void | addMotion (Motion *motion, Cell *cell, base::State *, base::EuclideanProjection &) |
Inserts the motion into the appropriate cell. | |
void | updateHeapElement (Motion *motion) |
Either update heap after motion's priority has changed or insert motion into heap. | |
Motion * | propagateFrom (Motion *motion, base::State *, base::State *) |
Select a state along motion and propagate a new motion from there. Return NULL if no valid motion could be generated starting at the selected state. | |
void | freeMemory () |
Protected Attributes | |
ompl::base::StateSamplerPtr | sampler_ |
State sampler. | |
RNG | rng_ |
std::vector< Motion * > | startMotions_ |
Vector holding all of the start states supplied for the problem Each start motion is the root of its own tree of motions. | |
ompl::BinaryHeap< Motion *, MotionCompare > | priorityQueue_ |
Priority queue of motions. | |
Cell * | bsp_ |
Binary Space Partition. | |
ompl::base::ProjectionEvaluatorPtr | projectionEvaluator_ |
Projection evaluator for the problem. | |
double | goalBias_ |
Number between 0 and 1 specifying the probability with which the goal should be sampled. | |
ompl::base::GoalSampleableRegion * | goalSampler_ |
Objected used to sample the goal. | |
unsigned int | iteration_ |
Iteration number and priority of the next Motion that will be generated. | |
Motion * | lastGoalMotion_ |
Closest motion to the goal. |
Detailed Description
Path-Directed Subdivision Tree.
- Short description
- PDST is a tree-based motion planner that attempts to detect the less explored area of the space through the use of a binary space partition of a projection of the state space. Exploration is biased towards large cells with few path segments. Unlike most tree-based planners which expand from a randomly select endpoint of a path segment, PDST expands from a randomly selected point along a deterministically selected path segment. It is important to set the projection the algorithm uses (setProjectionEvaluator() function). If no projection is set, the planner will attempt to use the default projection associated to the state space. An exception is thrown if no default projection is available either.
- External documentation
- A.M. Ladd and L.E. Kavraki, Motion planning in the presence of drift, underactuation and discrete system changes, in Robotics: Science and Systems I, pp. 233–241, MIT Press, June 2005. [[PDF]](http://www.roboticsproceedings.org/rss01/p31.pdf)
The documentation for this class was generated from the following files: