To address the issues of high sampling randomness, slow convergence speed, and insufficient path smoothness in traditional RRT* algorithm, this paper proposes a bidirectional APF-RRT* algorithm called BIAP-RRT*. First, a dynamic goal bias strategy is introduced to guide random sampling points towards the target direction, reducing ineffective sampling. Second, an improved artificial potential
... [Show full abstract] field method is incorporated to enhance the random tree’s exploration capability, enabling it to quickly escape from local optima. Third, a dual-tree growth strategy is adopted with an improved tree connection mechanism to accelerate algorithm convergence. Fourth, the path is pruned according to the triangle inequality to shorten path length, while B-spline curves combined with linear interpolation are used to smooth the pruned path, improving path quality. Finally, through comparative analysis in different environments, the BIAP-RRT* algorithm shows significant advantages over traditional RRT algorithm, RRT* algorithm, and an existing improved algorithm in terms of convergence speed, number of iterations, and path smoothness.
