Class ProjEST

Nested Relationships

Nested Types

Inheritance Relationships

Base Type

Class Documentation

class ProjEST : public ompl::base::Planner

Expansive Space Trees.

Short description

ProjEST is a tree-based motion planner that attempts to detect the less explored area of the space through the use of a grid imposed on a projection of the state space. Using this information, ProjEST continues tree expansion primarily from less explored areas. 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

D. Hsu, J.-C. Latombe, and R. Motwani, Path planning in expansive configuration spaces, Intl. J. Computational Geometry and Applications, vol. 9, no. 4-5, pp. 495–512, 1999. DOI: 10.1142/S0218195999000285[PDF]

Public Functions

ProjEST(const base::SpaceInformationPtr &si)

Constructor.

~ProjEST() override
virtual base::PlannerStatus solve(const base::PlannerTerminationCondition &ptc) override

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). If clearQuery() is called, the planner may retain prior datastructures generated from a previous query on a new problem definition. The function terminates if the call to ptc returns true.

virtual void clear() override

Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.

inline 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.

inline double getGoalBias() const

Get the goal bias the planner is using.

inline void setRange(double distance)

Set the range the planner is supposed to use.

This parameter greatly influences the runtime of the algorithm. It represents the maximum length of a motion to be added in the tree of motions.

inline double getRange() const

Get the range the planner is using.

inline void setProjectionEvaluator(const base::ProjectionEvaluatorPtr &projectionEvaluator)

Set the projection evaluator. This class is able to compute the projection of a given state.

inline void setProjectionEvaluator(const std::string &name)

Set the projection evaluator (select one from the ones registered with the state space).

inline const base::ProjectionEvaluatorPtr &getProjectionEvaluator() const

Get the projection evaluator.

virtual void setup() override

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 override

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).

Protected Types

using GridCell = Grid<MotionInfo>::Cell

A grid cell.

using CellPDF = PDF<GridCell*>

A PDF of grid cells.

Protected Functions

void freeMemory()

Free the memory allocated by this planner.

void addMotion(Motion *motion)

Add a motion to the exploration tree.

Motion *selectMotion()

Select a motion to continue the expansion of the tree from.

Protected Attributes

base::ValidStateSamplerPtr sampler_

Valid state sampler.

TreeData tree_

The exploration tree constructed by this algorithm.

base::ProjectionEvaluatorPtr projectionEvaluator_

This algorithm uses a discretization (a grid) to guide the exploration. The exploration is imposed on a projection of the state space.

double goalBias_ = {0.05}

The fraction of time the goal is picked as the state to expand towards (if such a state is available)

double maxDistance_ = {0.}

The maximum length of a motion to be added to a tree.

RNG rng_

The random number generator.

CellPDF pdf_

The PDF used for selecting a cell from which to sample a motion.

Motion *lastGoalMotion_ = {nullptr}

The most recent goal motion. Used for PlannerData computation.

class Motion

The definition of a motion.

Public Functions

Motion() = default
inline Motion(const base::SpaceInformationPtr &si)

Constructor that allocates memory for the state.

~Motion() = default

Public Members

base::State *state = {nullptr}

The state contained by the motion.

Motion *parent = {nullptr}

The parent motion in the exploration tree.

struct MotionInfo

A struct containing an array of motions and a corresponding PDF element.

Public Functions

inline Motion *operator[](unsigned int i)
inline const Motion *operator[](unsigned int i) const
inline void push_back(Motion *m)
inline unsigned int size() const
inline bool empty() const

Public Members

std::vector<Motion*> motions_
CellPDF::Element *elem_
struct TreeData

The data contained by a tree of exploration.

Public Functions

TreeData() = default

Public Members

Grid<MotionInfo> grid = {0}

A grid where each cell contains an array of motions.

unsigned int size = {0}

The total number of motions in the grid.