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Configure RRT* path planner

The `pathPlannerRRT`

object configures a vehicle path planner
based on the optimal rapidly exploring random tree (RRT*) algorithm. An RRT* path
planner explores the environment around the vehicle by constructing a tree of random
collision-free poses.

Once the `pathPlannerRRT`

object is configured, use the `plan`

function to plan a path from the start pose to the goal.

`planner = pathPlannerRRT(costmap)`

`planner = pathPlannerRRT(costmap,Name,Value)`

`planner = pathPlannerRRT(`

returns a `costmap`

)`pathPlannerRRT`

object for planning a vehicle path.
`costmap`

is a `vehicleCostmap`

object specifying the environment around the
vehicle. `costmap`

sets the `Costmap`

property value.

`planner = pathPlannerRRT(`

sets properties of the path planner by using one or more name-value pair
arguments. For example, `costmap`

,`Name,Value`

)`pathPlanner(costmap,'GoalBias',0.5)`

sets the `GoalBias`

property to a probability of 0.5. Enclose
each property name in quotes.

Updating any of the properties of the planner clears the planned path from

`pathPlannerRRT`

. Calling`plot`

displays only the costmap until a path is planned using`plan`

.To improve performance, the

`pathPlannerRRT`

object uses an approximate nearest neighbor search. This search technique checks only`sqrt(N)`

nodes, where`N`

is the number of nodes to search. To use exact nearest neighbor search, set the`ApproximateSearch`

property to`false`

.The Dubins and Reeds-Shepp connection methods are assumed to be kinematically feasible and ignore inertial effects. These methods make the path planner suitable for low velocity environments, where inertial effects of wheel forces are small.

[1] Karaman, Sertac, and Emilio Frazzoli. "Optimal Kinodynamic Motion Planning
Using Incremental Sampling-Based Methods." *49th IEEE Conference on Decision
and Control (CDC)*. 2010.

[2] Shkel, Andrei M., and Vladimir Lumelsky. "Classification of the Dubins Set."
*Robotics and Autonomous Systems*. Vol. 34, Number 4, 2001, pp.
179–202.

[3] Reeds, J. A., and L. A. Shepp. "Optimal paths for a car that goes both forwards
and backwards." *Pacific Journal of Mathematics*.
Vol. 145, Number 2, 1990, pp. 367–393.