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| LBTRRT (const base::SpaceInformationPtr &si) |
| Constructor.
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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).
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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). The function terminates if the call to ptc returns true.
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void | clear () override |
| Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.
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void | setGoalBias (double goalBias) |
| Set the goal bias. More...
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double | getGoalBias () const |
| Get the goal bias the planner is using.
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void | setRange (double distance) |
| Set the range the planner is supposed to use. More...
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double | getRange () const |
| Get the range the planner is using.
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template<template< typename T > class NN> |
void | setNearestNeighbors () |
| Set a different nearest neighbors datastructure.
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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.
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void | setApproximationFactor (double epsilon) |
| Set the apprimation factor.
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double | getApproximationFactor () const |
| Get the apprimation factor.
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std::string | getIterationCount () const |
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std::string | getBestCost () const |
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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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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().
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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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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 | considerEdge (Motion *parent, Motion *child, double c) |
| consider an edge for addition to the roadmap
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double | lazilyUpdateApxParent (Motion *child, Motion *parent) |
| lazily update the parent in the approximation tree without updating costs to cildren
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void | updateChildCostsApx (Motion *m, double delta) |
| update the child cost of the approximation tree
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void | removeFromParentApx (Motion *m) |
| remove motion from its parent in the approximation tree
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void | freeMemory () |
| Free the memory allocated by this planner.
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double | distanceFunction (const Motion *a, const Motion *b) const |
| Compute distance between motions (actually distance between contained states)
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bool | checkMotion (const Motion *a, const Motion *b) |
| local planner
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bool | checkMotion (const base::State *a, const base::State *b) |
| local planner
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Motion * | getMotion (std::size_t i) |
| get motion from id
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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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Lower Bound Tree Rapidly-exploring Random Trees.
- Short description
- LBTRRT (Lower Bound Tree RRT) is a near asymptotically-optimal incremental sampling-based motion planning algorithm. LBTRRT algorithm is guaranteed to converge to a solution that is within a constant factor of the optimal solution. The notion of optimality is with respect to the distance function defined on the state space we are operating on. See ompl::base::Goal::setMaximumPathLength() for how to set the maximally allowed path length to reach the goal. If a solution path that is shorter than ompl::base::Goal::getMaximumPathLength() is found, the algorithm terminates before the elapsed time.
- External documentation
- O. Salzman and D. Halperin, Sampling-based Asymptotically near-optimal RRT for fast, high-quality, motion planning, 2013. [PDF]
Definition at line 71 of file LBTRRT.h.