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| TRRT (const base::SpaceInformationPtr &si) |
| Constructor.
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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 &plannerTerminationCondition) |
| 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. More...
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virtual void | clear (void) |
| 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 (void) 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 (void) const |
| Get the range the planner is using.
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void | setMaxStatesFailed (double maxStatesFailed) |
| Set the maximum number of states that can be rejected before the temperature starts to rise.
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double | getMaxStatesFailed (void) const |
| Get the maximum number of states that can be rejected before the temperature starts to rise.
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void | setTempChangeFactor (double tempChangeFactor) |
| Set the factor by which the temperature rises or falls based on current acceptance/rejection rate.
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double | getTempChangeFactor (void) const |
| Get the factor by which the temperature rises or falls based on current acceptance/rejection rate.
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void | setMinTemperature (double minTemperature) |
| Set the minimum the temperature can drop to before being floored at that value.
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double | getMinTemperature (void) const |
| Get the minimum the temperature can drop to before being floored at that value.
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void | setInitTemperature (double initTemperature) |
| Set the initial temperature at the beginning of the algorithm. Should be low.
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double | getInitTemperature (void) const |
| Get the initial temperature at the beginning of the algorithm. Should be low.
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void | setFrontierThreshold (double frontier_threshold) |
| Set the distance between a new state and the nearest neighbor that qualifies that state as being a frontier.
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double | getFrontierThreshold (void) const |
| Get the distance between a new state and the nearest neighbor that qualifies that state as being a frontier.
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void | setFrontierNodeRatio (double frontierNodeRatio) |
| Set the ratio between adding nonfrontier nodes to frontier nodes, for example .1 is 1/10 or one nonfrontier node for every 10 frontier nodes added.
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double | getFrontierNodeRatio (void) const |
| Get the ratio between adding nonfrontier nodes to frontier nodes, for example .1 is 1/10 or one nonfrontier node for every 10 frontier nodes added.
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void | setKConstant (double kConstant) |
| Set the constant value used to normalize the expression.
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double | getKConstant (void) const |
| Get the constant value used to normalize the expression.
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template<template< typename T > class NN> |
void | setNearestNeighbors (void) |
| Set a different nearest neighbors datastructure.
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virtual void | setup (void) |
| 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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| Planner (const SpaceInformationPtr &si, const std::string &name) |
| Constructor.
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virtual | ~Planner (void) |
| Destructor.
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template<class T > |
T * | as (void) |
| Cast this instance to a desired type. More...
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template<class T > |
const T * | as (void) const |
| Cast this instance to a desired type. More...
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const SpaceInformationPtr & | getSpaceInformation (void) const |
| Get the space information this planner is using.
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const ProblemDefinitionPtr & | getProblemDefinition (void) const |
| Get the problem definition the planner is trying to solve.
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const PlannerInputStates & | getPlannerInputStates (void) 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 (void) 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 (void) const |
| Return the specifications (capabilities of this planner)
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virtual void | checkValidity (void) |
| 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 (void) const |
| Check if setup() was called for this planner.
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ParamSet & | params (void) |
| Get the parameters for this planner.
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const ParamSet & | params (void) const |
| Get the parameters for this planner.
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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 (void) |
| 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 | transitionTest (double childCost, double parentCost, double distance) |
| Filter irrelevant configuration regarding the search of low-cost paths before inserting into tree. More...
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bool | minExpansionControl (double randMotionDistance) |
| Use ratio to prefer frontier nodes to nonfrontier ones.
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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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base::StateSamplerPtr | sampler_ |
| State sampler.
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boost::shared_ptr
< NearestNeighbors< Motion * > > | nearestNeighbors_ |
| A nearest-neighbors datastructure containing the tree of motions.
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double | goalBias_ |
| The fraction of time the goal is picked as the state to expand towards (if such a state is available)
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double | maxDistance_ |
| The maximum length of a motion to be added to a tree.
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RNG | rng_ |
| The random number generator.
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Motion * | lastGoalMotion_ |
| The most recent goal motion. Used for PlannerData computation.
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bool | verbose_ |
| Output debug info.
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double | temp_ |
| Temperature parameter used to control the difficulty level of transition tests. Low temperatures limit the expansion to a slightly positive slopes, high temps enable to climb the steeper slopes. Dynamically tuned according to the information acquired during exploration.
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double | kConstant_ |
| Constant value used to normalize expression. Based on order of magnitude of the considered costs. Average cost of the query configurtaions since they are the only cost values known at the beginning of the search process.
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unsigned int | maxStatesFailed_ |
| Max number of rejections allowed.
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double | tempChangeFactor_ |
| Failure temperature factor used when max_num_failed_ failures occur.
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double | minTemperature_ |
| Prevent temperature from dropping too far.
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double | initTemperature_ |
| A very low value at initialization to authorize very easy positive slopes.
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unsigned int | numStatesFailed_ |
| Failure counter for states that are rejected.
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double | nonfrontierCount_ |
| Ratio counters for nodes that expand the search space versus those that do not.
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double | frontierCount_ |
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double | frontierThreshold_ |
| The distance between an old state and a new state that qualifies it as a frontier state.
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double | frontierNodeRatio_ |
| Target ratio of nonfrontier nodes to frontier nodes. rho.
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SpaceInformationPtr | si_ |
| The space information for which planning is done.
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ProblemDefinitionPtr | pdef_ |
| The user set problem definition.
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PlannerInputStates | pis_ |
| Utility class to extract valid input states.
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std::string | name_ |
| The name of this planner.
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PlannerSpecs | specs_ |
| The specifications of the planner (its capabilities)
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ParamSet | params_ |
| A map from parameter names to parameter instances for this planner. This field is populated by the declareParam() function.
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bool | setup_ |
| Flag indicating whether setup() has been called.
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Transition-based Rapidly-exploring Random Trees.
- Short description
- T-RRT is an RRT variant and tree-based motion planner that takes into consideration state costs to compute low-cost paths that follow valleys and saddle points of the configuration-space costmap. It uses transition tests from stoachastic optimization methods to accept or reject new potential sates.
- Example usage
- Please see Dave Coleman's example to see how TRRT can be used.
- External documentation
- L. Jaillet, J. Cortés, T. Siméon, Sampling-Based Path Planning on Configuration-Space Costmaps, in IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, NO. 4, AUGUST 2010. DOI: IEEE
[PDF]
Definition at line 77 of file TRRT.h.