BUG0-IRRT*: An Informed RRT* Path Planning Algorithm with BUG0-Initialized Sampling
Jialuo Jiang, Bing Fu, YY Li · 2025
This paper proposes a globally optimal path planning algorithm based on the Bug0 algorithm and an improved Informed-RRT* algorithm. To address the slow initial convergence speed of Informed-RRT*, the Bug0 algorithm is introduced as an initial path generator to rapidly produce an initial path segment, which is then fed into the Informed-RRT* algorithm. This approach significantly reduces the initial path generation time. Furthermore, a grid-based storage mechanism for random tree nodes is implemented to enhance the efficiency of parent node selection, further accelerating algorithm convergence. Comparative experiments in diverse environments demonstrate that the proposed algorithm outperforms RRT, RRT*, and Informed-RRT* in both computation time and path length. Theoretical analysis and simulation results confirm that the Bug0-Informed-RRT* algorithm delivers shorter paths and higher computational efficiency for path planning.