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May 7, 2026PLoS ONE0 citationsOpen Access

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

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TYTongzhu YuJWJiuHong WangDZDaiXiang Zhang

Key Points

  • To develop an effective path planning algorithm for crawler transport robots to improve operational safety and efficiency in coal mines.
  • Proposed an improved path planning algorithm based on the A* algorithm.
  • Utilized a bidirectional adaptive search strategy and terrain risk weights for global path optimization.
  • Integrated the DWA algorithm for enhanced real-time obstacle avoidance capability.
  • Conducted path planning experiments in a simulated environment.
  • The proposed algorithm significantly shortens the path length.
  • Effectively avoids various obstacles during navigation.
  • Demonstrates improved search efficiency and operational safety for transport robots.

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.

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Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/69fbef68164b5133a91a330dhttps://doi.org/10.1371/journal.pone.0342122
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