Integrated Global Path Planning for Autonomous Mobile Robots in Complicated Environments

Generating the optimal path curvature in complex environments and reducing the time cost of path planning are the key problems for global path planning. However, most of the existing methods based on graph-searching and optimization use inappropriate curvature calculation methods in the process of curvature optimization, which cannot ensure accurate path planning and optimal motion control, and redundant graph searches lead to a lot of time consumption. In this paper, we propose an integrated global path planning method, which can optimize the global path curvature to make the final trajectory more suitable for the structure of the environment. Besides, we also use the graph-searching method based on the high-definition map to fast search. We present the experimental re-sults of this method on different autonomous mobile platforms. The results showed that compared with the previous methods, the global path planning method proposed in this paper has better performance in complex path planning tasks, and can generate smoother global paths in less time.