Bi-RRT*: An Improved Bidirectional RRT* Path Planner for Robot in Two-Dimensional Space

Path planning is one of the fundamental issues in the research field of robot. In the last decades, Rapidly-exploring Random Tree star (RRT*) was one of the chosen path planner for robot with its probabilistically complete. In this paper, an improved bidirectional RRT* path planner for robot is proposed (Bi-RRT*), which has planned path with safety and smoothly guarantee. The main contributions of this paper include, firstly, combining the backtracking idea of the Quick-RRT algorithm with the greedy search strategy of the RRT-Connect algorithm, which can reduce the path cost and improve the operation efficiency of the algorithm. Second, in order to further reduce the running time of the algorithm, a new collision detection algorithm based on cross-product is proposed to replace the conventional collision detection strategy. To ensure the quality of the path, two post-processing strategies, path optimization strategy and path smoothing strategy, are proposed. Path optimization strategy is based on triangle inequality, and two optimization methods are proposed to effectively reduce the path cost. The path smoothing strategy based on the Bezier curve improves the continuity of a smooth arc and is better applied to path smoothing. Simulation results for both virtual and real environments show the advantages of combining Quick-RRT and RRT-Connect and verify the effectiveness of the proposed collision detection algorithm. Compared with similar algorithms, the proposed Bi-RRT algorithm has higher operational efficiency, smaller path cost, smoother planned paths, and improved path quality. (c) 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.