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using | Graph = boost::adjacency_list< boost::vecS, boost::vecS, boost::undirectedS, boost::property< vertex_state_t, base::State *, boost::property< vertex_total_connection_attempts_t, unsigned long int, boost::property< vertex_successful_connection_attempts_t, unsigned long int, boost::property< boost::vertex_predecessor_t, unsigned long int, boost::property< boost::vertex_rank_t, unsigned long int > >> >>, boost::property< boost::edge_weight_t, base::Cost > > |
| The underlying roadmap graph. More...
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using | Vertex = boost::graph_traits< Graph >::vertex_descriptor |
| The type for a vertex in the roadmap.
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using | Edge = boost::graph_traits< Graph >::edge_descriptor |
| The type for an edge in the roadmap.
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using | RoadmapNeighbors = std::shared_ptr< NearestNeighbors< Vertex > > |
| A nearest neighbors data structure for roadmap vertices.
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using | ConnectionStrategy = std::function< const std::vector< Vertex > &(const Vertex)> |
| A function returning the milestones that should be attempted to connect to.
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using | ConnectionFilter = std::function< bool(const Vertex &, const Vertex &)> |
| A function that can reject connections. More...
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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.
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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.
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| PRM (const base::SpaceInformationPtr &si, bool starStrategy=false) |
| Constructor.
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| PRM (const base::PlannerData &data, bool starStrategy=false) |
| Constructor.
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void | setProblemDefinition (const base::ProblemDefinitionPtr &pdef) override |
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void | setConnectionStrategy (const ConnectionStrategy &connectionStrategy) |
| Set the connection strategy function that specifies the milestones that connection attempts will be make to for a given milestone. More...
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void | setDefaultConnectionStrategy () |
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void | setMaxNearestNeighbors (unsigned int k) |
| Convenience function that sets the connection strategy to the default one with k nearest neighbors.
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unsigned int | getMaxNearestNeighbors () const |
| return the maximum number of nearest neighbors to connect a sample to More...
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void | setConnectionFilter (const ConnectionFilter &connectionFilter) |
| Set the function that can reject a milestone connection. More...
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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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void | constructRoadmap (const base::PlannerTerminationCondition &ptc) |
| While the termination condition allows, this function will construct the roadmap (using growRoadmap() and expandRoadmap(), maintaining a 2:1 ratio for growing/expansion of roadmap)
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void | growRoadmap (double growTime) |
| If the user desires, the roadmap can be improved for the given time (seconds). The solve() method will also improve the roadmap, as needed.
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void | growRoadmap (const base::PlannerTerminationCondition &ptc) |
| If the user desires, the roadmap can be improved until a given condition is true. The solve() method will also improve the roadmap, as needed.
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void | expandRoadmap (double expandTime) |
| Attempt to connect disjoint components in the roadmap using random bouncing motions (the PRM expansion step) for the given time (seconds).
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void | expandRoadmap (const base::PlannerTerminationCondition &ptc) |
| Attempt to connect disjoint components in the roadmap using random bouncing motions (the PRM expansion step) until the given condition evaluates true.
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base::PlannerStatus | solve (const base::PlannerTerminationCondition &ptc) override |
| Function that can solve the motion planning problem. Grows a roadmap using constructRoadmap(). 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. Start and goal states from the currently specified ProblemDefinition are cached. This means that between calls to solve(), input states are only added, not removed. When using PRM as a multi-query planner, the input states should be however cleared, without clearing the roadmap itself. This can be done using the clearQuery() function.
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void | clearQuery () override |
| Clear the query previously loaded from the ProblemDefinition. Subsequent calls to solve() will reuse the previously computed roadmap, but will clear the set of input states constructed by the previous call to solve(). This enables multi-query functionality for PRM.
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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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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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const Graph & | getRoadmap () const |
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unsigned long int | milestoneCount () const |
| Return the number of milestones currently in the graph.
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unsigned long int | edgeCount () const |
| Return the number of edges currently in the graph.
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const RoadmapNeighbors & | getNearestNeighbors () |
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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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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 () |
| Free all the memory allocated by the planner.
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Vertex | addMilestone (base::State *state) |
| Construct a milestone for a given state (state), store it in the nearest neighbors data structure and then connect it to the roadmap in accordance to the connection strategy.
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void | uniteComponents (Vertex m1, Vertex m2) |
| Make two milestones (m1 and m2) be part of the same connected component. The component with fewer elements will get the id of the component with more elements.
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bool | sameComponent (Vertex m1, Vertex m2) |
| Check if two milestones (m1 and m2) are part of the same connected component. This is not a const function since we use incremental connected components from boost.
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void | growRoadmap (const base::PlannerTerminationCondition &ptc, base::State *workState) |
| Randomly sample the state space, add and connect milestones in the roadmap. Stop this process when the termination condition ptc returns true. Use workState as temporary memory.
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void | expandRoadmap (const base::PlannerTerminationCondition &ptc, std::vector< base::State * > &workStates) |
| Attempt to connect disjoint components in the roadmap using random bounding motions (the PRM expansion step)
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void | checkForSolution (const base::PlannerTerminationCondition &ptc, base::PathPtr &solution) |
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bool | maybeConstructSolution (const std::vector< Vertex > &starts, const std::vector< Vertex > &goals, base::PathPtr &solution) |
| Check if there exists a solution, i.e., there exists a pair of milestones such that the first is in start and the second is in goal, and the two milestones are in the same connected component. If a solution is found, it is constructed in the solution argument.
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ompl::base::Cost | constructApproximateSolution (const std::vector< Vertex > &starts, const std::vector< Vertex > &goals, base::PathPtr &solution) |
| (Assuming that there is always an approximate solution), finds an approximate solution.
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bool | addedNewSolution () const |
| Returns the value of the addedNewSolution_ member.
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base::PathPtr | constructSolution (const Vertex &start, const Vertex &goal) |
| Given two milestones from the same connected component, construct a path connecting them and set it as the solution.
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base::Cost | costHeuristic (Vertex u, Vertex v) const |
| Given two vertices, returns a heuristic on the cost of the path connecting them. This method wraps OptimizationObjective::motionCostHeuristic.
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double | distanceFunction (const Vertex a, const Vertex b) const |
| Compute distance between two milestones (this is simply distance between the states of the milestones)
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std::string | getIterationCount () const |
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std::string | getBestCost () const |
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std::string | getMilestoneCountString () const |
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std::string | getEdgeCountString () 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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Probabilistic RoadMap planner.
- Short description
- PRM is a planner that constructs a roadmap of milestones that approximate the connectivity of the state space. The milestones are valid states in the state space. Near-by milestones are connected by valid motions. Finding a motion plan that connects two given states is reduced to a discrete search (this implementation uses A*) in the roadmap.
- External documentation
- L.E. Kavraki, P.Švestka, J.-C. Latombe, and M.H. Overmars, Probabilistic roadmaps for path planning in high-dimensional configuration spaces, IEEE Trans. on Robotics and Automation, vol. 12, pp. 566–580, Aug. 1996. DOI: 10.1109/70.508439
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Definition at line 112 of file PRM.h.