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| XXL (const base::SpaceInformationPtr &si) |
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| XXL (const base::SpaceInformationPtr &si, const XXLDecompositionPtr &decomp) |
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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).
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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.
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virtual void | clear () |
| | Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.
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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.
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void | setDecomposition (const XXLDecompositionPtr &decomp) |
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double | getRandWalkRate () const |
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void | setRandWalkRate (double rate) |
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| Planner (const Planner &)=delete |
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Planner & | operator= (const Planner &)=delete |
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| Planner (SpaceInformationPtr si, std::string name) |
| | Constructor.
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virtual | ~Planner ()=default |
| | Destructor.
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| template<class T > |
| T * | as () |
| | Cast this instance to a desired type. More...
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| template<class T > |
| const T * | as () const |
| | Cast this instance to a desired type. More...
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const SpaceInformationPtr & | getSpaceInformation () const |
| | Get the space information this planner is using.
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const ProblemDefinitionPtr & | getProblemDefinition () const |
| | Get the problem definition the planner is trying to solve.
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ProblemDefinitionPtr & | getProblemDefinition () |
| | Get the problem definition the planner is trying to solve.
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const PlannerInputStates & | getPlannerInputStates () const |
| | Get the planner input states.
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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().
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PlannerStatus | solve (const PlannerTerminationConditionFn &ptc, double checkInterval) |
| | Same as above except the termination condition is only evaluated at a specified interval.
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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.
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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().
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const std::string & | getName () const |
| | Get the name of the planner.
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void | setName (const std::string &name) |
| | Set the name of the planner.
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const PlannerSpecs & | getSpecs () const |
| | Return the specifications (capabilities of this planner)
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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.
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bool | isSetup () const |
| | Check if setup() was called for this planner.
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ParamSet & | params () |
| | Get the parameters for this planner.
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const ParamSet & | params () const |
| | Get the parameters for this planner.
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const PlannerProgressProperties & | getPlannerProgressProperties () const |
| | Retrieve a planner's planner progress property map.
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virtual void | printProperties (std::ostream &out) const |
| | Print properties of the motion planner.
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virtual void | printSettings (std::ostream &out) const |
| | Print information about the motion planner's settings.
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void | freeMemory () |
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void | allocateLayers (Layer *layer) |
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void | updateRegionConnectivity (const Motion *m1, const Motion *m2, int layer) |
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Layer * | getLayer (const std::vector< int > ®ions, int layer) |
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int | addState (const base::State *state) |
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int | addThisState (base::State *state) |
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int | addGoalState (const base::State *state) |
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int | addStartState (const base::State *state) |
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void | updateRegionProperties (const std::vector< int > ®ions) |
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void | updateRegionProperties (Layer *layer, int region) |
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void | sampleStates (Layer *layer, const ompl::base::PlannerTerminationCondition &ptc) |
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bool | sampleAlongLead (Layer *layer, const std::vector< int > &lead, const ompl::base::PlannerTerminationCondition &ptc) |
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int | steerToRegion (Layer *layer, int from, int to) |
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int | expandToRegion (Layer *layer, int from, int to, bool useExisting=false) |
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bool | feasibleLead (Layer *layer, const std::vector< int > &lead, const ompl::base::PlannerTerminationCondition &ptc) |
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bool | connectLead (Layer *layer, const std::vector< int > &lead, std::vector< int > &candidateRegions, const ompl::base::PlannerTerminationCondition &ptc) |
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void | connectRegion (Layer *layer, int region, const base::PlannerTerminationCondition &ptc) |
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void | connectRegions (Layer *layer, int r1, int r2, const base::PlannerTerminationCondition &ptc, bool all=false) |
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void | computeLead (Layer *layer, std::vector< int > &lead) |
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| bool | searchForPath (Layer *layer, const ompl::base::PlannerTerminationCondition &ptc) |
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void | getNeighbors (int rid, const std::vector< double > &weights, std::vector< std::pair< int, double >> &neighbors) const |
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bool | shortestPath (int r1, int r2, std::vector< int > &path, const std::vector< double > &weights) |
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bool | randomWalk (int r1, int r2, std::vector< int > &path) |
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void | getGoalStates () |
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void | getGoalStates (const base::PlannerTerminationCondition &ptc) |
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bool | constructSolutionPath () |
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bool | isStartState (int idx) const |
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bool | isGoalState (int idx) const |
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void | writeDebugOutput () const |
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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.
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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.
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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.
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XXL is a probabilistically complete sampling-based algorithm designed to plan the motions of high-dimensional mobile manipulators and related platforms. Using a novel sampling and connection strategy that guides a set of points mapped on the robot through the workspace, XXL scales to realistic manipulator platforms with dozens of joints by focusing the search of the robot's configuration space to specific degrees-of-freedom that affect motion in particular portions of the workspace. Simulated planning scenarios with the Robonaut2 platform and planar kinematic chains confirm that XXL exhibits competitive solution times relative to many existing works while obtaining execution-quality solution paths. Solutions from XXL are of comparable quality to costaware methods even though XXL does not explicitly optimize over any particular criteria, and are computed in an order of magnitude less time.
- 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
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Definition at line 128 of file XXL.h.
Public Member Functions inherited from ompl::base::Planner