#include <LazyRRT.h>
Classes | |
class | Motion |
Representation of a motion. More... | |
Public Member Functions | |
LazyRRT (const base::SpaceInformationPtr &si) | |
Constructor. | |
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 bool | 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 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. | |
virtual void | clear (void) |
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 biasing. | |
double | getGoalBias (void) const |
Get the goal bias the planner is using. | |
void | setRange (double distance) |
Set the range the planner is supposed to use. | |
double | getRange (void) const |
Get the range the planner is using. | |
template<template< typename T > class NN> | |
void | setNearestNeighbors (void) |
Set a different nearest neighbors datastructure. | |
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. | |
Protected Member Functions | |
void | freeMemory (void) |
Free the memory allocated by this planner. | |
void | removeMotion (Motion *motion) |
Remove a motion from the tree datastructure. | |
double | distanceFunction (const Motion *a, const Motion *b) const |
Compute distance between motions (actually distance between contained states) | |
Protected Attributes | |
base::StateSamplerPtr | sampler_ |
State sampler. | |
boost::shared_ptr < NearestNeighbors< Motion * > > | nn_ |
A nearest-neighbors datastructure containing the tree of motions. | |
double | goalBias_ |
The fraction of time the goal is picked as the state to expand towards (if such a state is available) | |
double | maxDistance_ |
The maximum length of a motion to be added to a tree. | |
RNG | rng_ |
The random number generator. |
Lazy RRT.
@par Short description RRT is a tree-based motion planner that uses the following idea: RRT samples a random state @b qr in the state space, then finds the state @b qc among the previously seen states that is closest to @b qr and expands from @b qc towards @b qr, until a state @b qm is reached. @b qm is then added to the exploration tree. The difference between \ref gRRT "RRT" and LazyRRT is that when moving towards the new state @b qm, LazyRRT does not check to make sure the path is valid. Instead, it is optimistic and attempts to find a path as soon as possible. Once a path is found, it is checked for collision. If collisions are found, the invalid path segments are removed and the search process is continued. @par External documentation - J. Kuffner and S.M. LaValle, RRT-connect: An efficient approach to single-query path planning, in <em>Proc. 2000 IEEE Intl. Conf. on Robotics and Automation</em>, pp. 995–1001, Apr. 2000. DOI: <a href="http://dx.doi.org/10.1109/ROBOT.2000.844730">10.1109/ROBOT.2000.844730</a><br> <a href="http://ieeexplore.ieee.org/ielx5/6794/18246/00844730.pdf?tp=&arnumber=844730&isnumber=18246">[PDF]</a> <a href="http://msl.cs.uiuc.edu/~lavalle/rrtpubs.html">[more]</a> - R. Bohlin and L.E. Kavraki, A Randomized Algorithm for Robot Path Planning Based on Lazy Evaluation, in <em>Handbook on Randomized Computing</em>, pp. 221–249, 2001.<br> <a href="http://www.kavrakilab.org/sites/default/files/bohlin2001lazy-evaluation.pdf">[PDF]</a> - R. Bohlin and L.E. Kavraki, Path planning using lazy PRM, in <em>Proc. 2000 IEEE Intl. Conf. on Robotics and Automation</em>, pp. 521–528, 2000. DOI: <a href="http://dx.doi.org/10.1109/ROBOT.2000.844107">10.1109/ROBOT.2000.844107</a><br> <a href="http://ieeexplore.ieee.org/ielx5/6794/18235/00844107.pdf?tp=&arnumber=844107&isnumber=18235">[PDF]
void ompl::geometric::LazyRRT::setGoalBias | ( | double | goalBias | ) | [inline] |
Set the goal biasing.
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.
void ompl::geometric::LazyRRT::setRange | ( | double | distance | ) | [inline] |