Range-Limited Random Tree (Ryan Luna's Random Tree) More...

#include <ompl/geometric/planners/rlrt/RLRT.h>

Inheritance diagram for ompl::geometric::RLRT:

Classes

class  Motion
 A motion (tree node) with parent pointer. More...
 

Public Member Functions

 RLRT (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 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). 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 ()
 Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.
 
void setGoalBias (double goalBias)
 Set the goal bias 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.
 
void setRange (double distance)
 Set the maximum distance between states in the tree.
 
double getRange () const
 Get the maximum distance between states in the tree.
 
bool getKeepLast () const
 If true, the planner will not have the range limitation. Instead, if a collision is detected, the last valid state is retained.
 
void setKeepLast (bool keepLast)
 Set whether the planner will use the range or keep last heuristic. If keepLast = false, motions are limited in distance to range_, otherwise the last valid state is retained when a collision is detected.
 
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.
 
- Public Member Functions inherited from ompl::base::Planner
 Planner (const Planner &)=delete
 
Planneroperator= (const Planner &)=delete
 
 Planner (SpaceInformationPtr si, std::string name)
 Constructor.
 
virtual ~Planner ()=default
 Destructor.
 
template<class T >
T * as ()
 Cast this instance to a desired type. More...
 
template<class T >
const T * as () const
 Cast this instance to a desired type. More...
 
const SpaceInformationPtrgetSpaceInformation () const
 Get the space information this planner is using.
 
const ProblemDefinitionPtrgetProblemDefinition () const
 Get the problem definition the planner is trying to solve.
 
ProblemDefinitionPtrgetProblemDefinition ()
 Get the problem definition the planner is trying to solve.
 
const PlannerInputStatesgetPlannerInputStates () const
 Get the planner input states.
 
virtual void setProblemDefinition (const ProblemDefinitionPtr &pdef)
 Set the problem definition for the planner. The problem needs to be set before calling solve(). Note: If this problem definition replaces a previous one, it may also be necessary to call clear() or clearQuery().
 
PlannerStatus solve (const PlannerTerminationConditionFn &ptc, double checkInterval)
 Same as above except the termination condition is only evaluated at a specified interval.
 
PlannerStatus solve (double solveTime)
 Same as above except the termination condition is solely a time limit: the number of seconds the algorithm is allowed to spend planning.
 
virtual void clearQuery ()
 Clears internal datastructures of any query-specific information from the previous query. Planner settings are not affected. The planner, if able, should retain all datastructures generated from previous queries that can be used to help solve the next query. Note that clear() should also clear all query-specific information along with all other datastructures in the planner. By default clearQuery() calls clear().
 
const std::string & getName () const
 Get the name of the planner.
 
void setName (const std::string &name)
 Set the name of the planner.
 
const PlannerSpecsgetSpecs () const
 Return the specifications (capabilities of this planner)
 
virtual void checkValidity ()
 Check to see if the planner is in a working state (setup has been called, a goal was set, the input states seem to be in order). In case of error, this function throws an exception.
 
bool isSetup () const
 Check if setup() was called for this planner.
 
ParamSetparams ()
 Get the parameters for this planner.
 
const ParamSetparams () const
 Get the parameters for this planner.
 
const PlannerProgressPropertiesgetPlannerProgressProperties () const
 Retrieve a planner's planner progress property map.
 
virtual void printProperties (std::ostream &out) const
 Print properties of the motion planner.
 
virtual void printSettings (std::ostream &out) const
 Print information about the motion planner's settings.
 

Protected Member Functions

void freeMemory ()
 Free the memory allocated by this planner.
 
- Protected Member Functions inherited from ompl::base::Planner
template<typename T , typename PlannerType , typename SetterType , typename GetterType >
void declareParam (const std::string &name, const PlannerType &planner, const SetterType &setter, const GetterType &getter, const std::string &rangeSuggestion="")
 This function declares a parameter for this planner instance, and specifies the setter and getter functions.
 
template<typename T , typename PlannerType , typename SetterType >
void declareParam (const std::string &name, const PlannerType &planner, const SetterType &setter, const std::string &rangeSuggestion="")
 This function declares a parameter for this planner instance, and specifies the setter function.
 
void addPlannerProgressProperty (const std::string &progressPropertyName, const PlannerProgressProperty &prop)
 Add a planner progress property called progressPropertyName with a property querying function prop to this planner's progress property map.
 

Protected Attributes

base::StateSamplerPtr sampler_
 State sampler.
 
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 range_ {0.}
 The maximum length of a motion to be added to a tree.
 
bool keepLast_ {false}
 If true, the planner will retain the last valid state during local planner. Default is false.
 
RNG rng_
 The random number generator.
 
MotionlastGoalMotion_ {nullptr}
 The most recent goal motion. Used for PlannerData computation.
 
std::vector< Motion * > motions_
 
- Protected Attributes inherited from ompl::base::Planner
SpaceInformationPtr si_
 The space information for which planning is done.
 
ProblemDefinitionPtr pdef_
 The user set problem definition.
 
PlannerInputStates pis_
 Utility class to extract valid input states

 
std::string name_
 The name of this planner.
 
PlannerSpecs specs_
 The specifications of the planner (its capabilities)
 
ParamSet params_
 A map from parameter names to parameter instances for this planner. This field is populated by the declareParam() function.
 
PlannerProgressProperties plannerProgressProperties_
 A mapping between this planner's progress property names and the functions used for querying those progress properties.
 
bool setup_
 Flag indicating whether setup() has been called.
 

Additional Inherited Members

- Public Types inherited from ompl::base::Planner
using PlannerProgressProperty = std::function< std::string()>
 Definition of a function which returns a property about the planner's progress that can be queried by a benchmarking routine.
 
using PlannerProgressProperties = std::map< std::string, PlannerProgressProperty >
 A dictionary which maps the name of a progress property to the function to be used for querying that property.
 

Detailed Description

Range-Limited Random Tree (Ryan Luna's Random Tree)

RLRT is a basic tree-based planner without any sophistic heuristics to guide the exploration. It should be used as a baseline for comparison against other tree-based planners. In high-dimensional search spaces it can sometimes perform surprisingly well.

Associated publication:
R. Luna, M. Moll, J. Badger, and L. E. Kavraki, A Scalable Motion Planner for High-Dimensional Kinematic Systems, Intl. J. of Robotics Research, vol. 39, issue 4, pp. 361-388, Mar. 2020. DOI: 10.1177/0278364919890408
[PDF]

Definition at line 63 of file RLRT.h.


The documentation for this class was generated from the following files:
  • ompl/geometric/planners/rlrt/RLRT.h
  • ompl/geometric/planners/rlrt/src/RLRT.cpp