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### Highlights fromMultiple Rapidly-exploring Random Tree (RRT)

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# Multiple Rapidly-exploring Random Tree (RRT)

by Gavin

15 Sep 2008 (Updated 14 Mar 2013)

Multiple RRT implementation for mobile robot path planning or C-space manipulator motion planning

File Information
Description

% See Usage section in RrtPlanner.m file. This is a basic example of usage:

treesMax = 28; %How many multiple trees (must be at least 2, 1 for source and 1 for destination

seedsPerAxis = 3; %Number of seeds allowed on each axis (discretely placed seeds which idealy helps the RRT expansion)

wallCount = 5; %Number of mock walls to be placed in the environment

rrt = RrtPlanner(treesMax,seedsPerAxis,wallCount)
rrt.SetStart([0 -0.9 0]);
rrt.SetGoal([0 +0.9 0]);
rrt.Run()
plot3(rrt.smoothedPath(:,1),rrt.smoothedPath(:,2),rrt.smoothedPath(:,3),'k*');
delete(rrt);

obstacleFilename = 'obstacles.txt';
seedsPerAxis = 7;
treesMax = seedsPerAxis^3*3+2;
rrt = RrtPlanner(treesMax,seedsPerAxis,obstacleFilename);
rrt.drawingSkipsPerDrawing = 30;
rrt = RrtPlanner(treesMax,seedsPerAxis,obstacleFilename);
rrt.Run()
plot3(rrt.path(:,1),rrt.path(:,2),rrt.path(:,3),'k*');

% To generate an obstacle: create them by specifying rectangular planes as a set of 4 points around the bounds of a rectangle
A-------- B
| |
| |
| |
D---------C

% If this is flat on the z plane at 0.5 then the file would look something like this (with the x,y,z of A, B, C, D on separate lines)
0 0 0.5
1 0 0.5
1 1 0.5
0 1 0.5

A YouTube video of a simple case of this planner can be found here:
http://youtu.be/LodUn86QAfg

RRTs first published in [1] are randomised planners especially adept at solving difficult,high-dimensional path planning problems. However, environments with low-connectivity due to the presence of obstacles can severely affect convergence. Multiple RRTs have been proposed as a means of addressing this issue, however, this approach can adversely affect computational efficiency.

This paper [2] published by the authors of this Matlab code is the implementation of multiple Rapidly-exploring Random Tree (RRT) algorithm work. This paper introduces a new and simple method which takes advantage of the benefits of multiple trees, whilst ensuring the computational burden of maintaining them is minimised. Results indicate that multiple RRTs are able to reduce the logarithmic complexity of the search, most notably in environments with high obstacle densities.

[1] LaValle, S. M., ‘Rapidly-Exploring Random Trees: A New Tool for Path Planning’, TR 98-11, Computer Science Department, Iowa State University, Oct. 1998.
[2] Matthew Clifton, Gavin Paul, Ngai Kwok, Dikai Liu, Da-Long Wang, "Evaluating Performance of Multiple RRTs", IEEE conference on Mechatronic and Embedded Systems and Application, 2008

MATLAB release MATLAB 7.11 (R2010b)
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12 May 2012
23 Apr 2012
30 Jan 2012

Dear Gavin, thanks for providing this code. It would be easier to understand and implement if you would add a complete description of all arguments in the header of each function - the same way Matlab does.

There are also name collisions, 'connect' is just too generic. A good workaround is to use a prefix such as 'rrt_' to make function names more unique and to simplify renaming.

10 Nov 2011

Thank You very much sir.

04 Nov 2011

05 Aug 2011

The file could be helpful for me.Tkank you

18 Sep 2008

I've been searching for RRT matlab implementation for quite a while. Thanks for your effort