Research on Optimal Sampling and Path Planning Algorithm of Static Map Based on Dubins Curve
Chenxi Liao · 2024
This study is devoted to the research of optimal sampling and path planning algorithms of static maps based on Dubins curve. Dubins curve, a geometric curve with minimum path length, has been widely used in path planning for mobile robots and autonomous vehicles. This study first proposes a sampling point optimization strategy based on the curvature-sensitive algorithm. By analyzing the curvature distribution of the static map, the optimal location and number of sampling points are determined to achieve efficient coverage of the map. Then, combined with the heuristic search algorithm, we design an effective path planning method, which can use the characteristics of the Dubins curve to find the optimal path from the starting point to the target point under the premise of satisfying the constraints. By combining curvature sensitive algorithm and a heuristic search algorithm, this study not only improves the representativeness and coverage of sampling points but also optimizes the efficiency and accuracy of path planning. The experimental results show that the algorithm has achieved remarkable results in the sampling and path planning of static maps and provides strong support for the application of mobile robots and autonomous driving.