Floyd-Assisted RRT* for Path Planning in Static Environment

Rapidly Random-exploring Tree (RRT) algorithm has been widely applied in path planning for robots, autonomous vehicles, and other applications. However, the traditional RRT algorithm needs to reconstruct the exploration tree and expand from the root node for each path planning task even in a static environment, resulting in low exploration efficiency and slow convergence speed. To address this issue, we propose a Floyd-assisted RRT* algorithm. Firstly, critical nodes are pre-searched. Then shortest trees are constructed based on Floyd algorithm. Finally, when a path planning task arises, an initial path is determined based on the shortest path trees, and RRT* algorithm is used to optimize the path. The simulation results reveal that the Floyd-assisted RRT* generates shorter paths and requires less computational time.