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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

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

TongZhu Yu¹, JiuHong Wang¹, DaiXiang Zhang¹

¹Yankuang Energy Group Co., Ltd, Jining, China.

|May 4, 2026

Summary

This study introduces an improved A* path planning algorithm for safe and efficient robot navigation in complex coal mine roadways. The enhanced algorithm optimizes routes, avoids hazards, and ensures operational safety for underground material transport.

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Area of Science:

Robotics
Artificial Intelligence
Mining Engineering

Background:

Coal mines require efficient and safe underground material transportation.
Unstructured mine roadways pose significant challenges for robotic navigation.
Existing path planning algorithms may not fully address the complexities of mine environments.

Purpose of the Study:

To develop an improved path planning algorithm for intelligent coal mine construction.
To enhance both driving efficiency and operational safety of robots in complex mine roadways.
To provide a viable solution for path planning and navigation of tracked transport robots.

Main Methods:

An improved A* algorithm integrating global and local path planning.
A bidirectional adaptive search strategy for enhanced global path efficiency.
Terrain risk weights incorporated into the cost function for hazard avoidance.
Dynamic Window Approach (DWA) algorithm for real-time local obstacle avoidance.

Main Results:

The proposed algorithm effectively avoids various obstacles in simulated mine roadways.
Significant reductions in path length and search time were achieved.
The algorithm demonstrated successful global path optimization and local safety assurance.
Path planning experiments validated the algorithm's effectiveness.

Conclusions:

The improved A* algorithm offers a robust solution for robot path planning in complex mine environments.
The collaborative global-local approach enhances navigation efficiency and safety.
This research contributes to the advancement of intelligent construction in coal mines.