Application of RRT-based local Path Planning Algorithm in Unknown Environment

Path planning for mobile robots has received a great deal of attention over the past two decades. The basic rapidly-exploring random tree (RRT) algorithm is famous in this field because it excels at exploring free space in the large environments and it is parallelizable. In this paper, we applied modified RRT algorithm to local navigation of a mobile robot in unknown environment. The biased direction from RRT algorithm is used to reduce the nodes and therefore the amount of calculation is decreased for real-time computation. We conducted the simulation and simple real-time experiments to verify the proposed method in real unknown environment.