Sampling based motion planning algorithm, Rapidly Exploring Random Trees, has been a hot research topic in the last decade. Recently researchers introduced a probabilistically optimal version of the RRT algorithm called RRT*. ARMS Lab researchers, Olzhas Adiyatov and Atakan Varol, developed a memory efficient variant of RRT* motion planning algorithm. To allow the usage and benchmarking of the RRT*FN for various problems in robotics and mechatronics, ARMS Lab launches a Matlab toolset. The package also allows the usage of the traditional RRT and RRT* algorithms as well. Multiple demo problems are included in the package to provide users example to implement the algorithm for their own research problems. For more information and download, please visit the RRT*FN page.