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RRT

Class for rapidly-exploring random tree navigation

A concrete subclass of the Navigation class that implements the rapidly exploring random tree (RRT) algorithm. This is a kinodynamic planner that takes into account the motion constraints of the vehicle.

Methods

plan Compute the tree
path Compute a path
plot Display the tree
display Display the parameters in human readable form
char Convert to string

Example

goal = [0,0,0];
start = [0,2,0];
veh = Vehicle([], 'stlim', 1.2);
rrt = RRT([], veh, 'goal', goal, 'range', 5);
rrt.plan()             % create navigation tree
rrt.path(start, goal)  % animate path from this start location

Robotics, Vision & Control compatability mode:

goal = [0,0,0];
start = [0,2,0];
rrt = RRT();           % create navigation object
rrt.plan()             % create navigation tree
rrt.path(start, goal)  % animate path from this start location

References

See also

Navigation, PRM, DXform, Dstar, PGraph


RRT.RRT

Create a RRT navigation object

R = RRT.RRT(map, veh, options) is a rapidly exploring tree navigation object for a region with obstacles defined by the map object map.

R = RRT.RRT() as above but internally creates a Vehicle class object and does not support any map or options. For compatibility with RVC book.

Options

'npoints', N Number of nodes in the tree
'time', T Period to simulate dynamic model toward random point
'range', R Specify rectangular bounds
'goal', P Goal position (1x2) or pose (1x3) in workspace
'speed', S Speed of vehicle [m/s] (default 1)
'steermax', S Maximum steer angle of vehicle [rad] (default 1.2)

Notes

Reference

See also

Vehicle


RRT.char

Convert to string

R.char() is a string representing the state of the RRT object in human-readable form.

invoke the superclass char() method


RRT.path

Find a path between two points

x = R.path(start, goal) finds a path (Nx3) from state start (1x3) to the goal (1x3).

P.path(start, goal) as above but plots the path in 3D. The nodes are shown as circles and the line segments are blue for forward motion and red for backward motion.

Notes


RRT.plan

Create a rapidly exploring tree

R.plan(options) creates the tree roadmap by driving the vehicle model toward random goal points. The resulting graph is kept within the object.

Options

'goal', P Goal pose (1x3)
'noprogress' Don't show the progress bar
'samples' Show samples

RRT.plot

Visualize navigation environment

R.plot() displays the navigation tree in 3D.


 

© 1990-2012 Peter Corke.