Utilizing Relaxed A* and Adaptive Window Approach toward Hybrid Path Planning for Autonomous Mobile Robots
Keita Tsuge, Takuto Sakuma, Shōhei Kato · 2023
In recent years, demand for path planning solutions for autonomous mobile robots has increased. Particularly, challenges such as reducing execution time in large-scale environments and ensuring safety for humans have been identified. In this paper, we address these challenges by employing hybrid path planning, which combines global path planning and local path planning, and improving the global path planning aspect. Through simulation experiments, we confirmed that the proposed system reduces execution time and path length while ensuring safety.