RRTs first published in  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  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.
 LaValle, S. M., ‘Rapidly-Exploring Random Trees: A New Tool for Path Planning’, TR 98-11, Computer Science Department, Iowa State University, Oct. 1998.
 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
For those struggling with running the code, the download is just a function file. You should create a new file an call the function from there or just straight from the command window. The RrtPlanner.m file has the example in the comments on how to run the path planner.
Basically just create a new .m file in the same directory and copy (example) commands:
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]);
Dear Gavin. Thanks for the code. However, I have been trying to run it without success. The program only gives me a 3D plot of the obstacles and the start and final points. I debugged the code and found the functions for RRT search does not come in the loop. Is there a way that you can help me run the code?
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.