Research on path planning algorithms for Crawler transport robots in complex tunnels.

Abstract

To meet the demand for efficient and safe underground material transportation in the intelligent construction of coal mines, addressing the unstructured environmental characteristics of mine roadways, this study proposes an improved path planning algorithm based on the A* algorithm. It aims to achieve the dual requirements of driving efficiency and operational safety for robots in complex environments. The algorithm adopts a collaborative architecture combining global and local path planning: at the global level, it enhances search efficiency by introducing a bidirectional adaptive search strategy and incorporates terrain risk weights into the cost function, enabling the planned path to effectively avoid high-risk areas and achieve global path optimization; at the local level, it integrates the DWA algorithm to strengthen the robot's real-time obstacle avoidance capability and ensure operational safety. To validate the algorithm's effectiveness, path planning experiments were conducted in a simulated environment. The results demonstrate that the proposed algorithm effectively avoids various obstacles, significantly shortens path length and search time, providing a viable solution for path planning and navigation of tracked transport robots in complex roadways.