BRRT-CHS: Contour-Guided Hybrid Sampling for Path Planning in Diverse Environments

To tackle the inefficiency of free space representation and the low sampling efficiency of path planning algorithms in complex environments,a novel method is proposed for extracting safe airspace pro-files and generating global path guidance. To start with, to address the issue of spatial seed sampling in complex environments, a regional preference seed point sampling strategy is designed to enhance the computational performance of large-scale airspace ex-traction. Furthermore, a KD-tree spatial optimization strategy combined with OpenMP parallel acceleration is proposed, significantly enhancing the sampling effi-ciency. On this basis, a Bi-RRT approach with Contour-guided Hybrid Sampling (BRRT-CHS) is proposed, demonstrating significant improvements in both search efficiency and success rate, particularly in complex environments. The simulation experiment results show that this method effectively represents complex free space, improving the success rate and quality of global path guidance.