An Improvement of the Rapidly-Exploring Random Tree Method for Path Planning of a Car-Like Robot in Virtual Environment
In this paper we present a method of reducing the computational complexity necessary in path planning for a car-like robot in order to generate the optimal path according to the constrains set by the user. The proposed method implies adding the following constrains: setting the maximum and minimum distance between the possible paths and the obstacles placed in the virtual environment in order to reduce the simulation time and to obtain a real-time application and to remove the paths that contain unnecessary turns around the environment without avoiding an obstacle. By applying this method the simulation complexity is reduced and the optimal path is easier to find.
Prof. Adrian Olaru
T. Gîrbacia and G. Mogan, "An Improvement of the Rapidly-Exploring Random Tree Method for Path Planning of a Car-Like Robot in Virtual Environment", Applied Mechanics and Materials, Vol. 772, pp. 471-476, 2015