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Related Experiment Video

Updated: May 17, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

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Published on: January 20, 2023

Path Planning in Narrow Road Scenarios Based on Four-Layer Network Cost Structure Map.

Ping Wang^1,2, Hao Zhang¹, Youming Tang³

¹School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361024, China.

Sensors (Basel, Switzerland)

|May 14, 2025

Summary

This study introduces a novel path planning method for automated guided vehicles (AGVs) in narrow spaces. The approach enhances safety and efficiency by integrating Voronoi skeletons into cost maps, improving AGV navigation.

Keywords:

B-spline smoothing Voronoi layer four-layer network structure narrow roads path planning

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Area of Science:

Robotics
Artificial Intelligence
Computer Science

Background:

Automated Guided Vehicle (AGV) path planning in narrow environments faces challenges with safety distances and path smoothness.
Traditional cost map methods struggle to adequately address the complexities of confined spaces.

Purpose of the Study:

To develop an improved path planning algorithm for AGVs specifically designed for narrow road scenarios.
To enhance the safety, efficiency, and robustness of AGV navigation in constrained environments.

Main Methods:

Integration of Voronoi-skeleton-based custom layers with traditional cost maps to create a four-layer network cost map.
Application of an improved A* algorithm for global path planning and B-spline smoothing for path optimization.
Extraction of key Voronoi skeleton nodes to generate a custom layer for accurate obstacle influence distinction.

Main Results:

Achieved an 82% improvement in AGV path planning safety in narrow road scenarios.
Reduced the number of spatial turning points by 55.85%, leading to smoother trajectories.
Shortened path planning time by 48.98%, enhancing real-time performance.

Conclusions:

The proposed method significantly enhances the robustness and real-time performance of AGV path planning in narrow roads.
The integrated Voronoi-skeleton and cost map approach ensures safer and more optimal AGV movement.
This algorithm provides a viable solution for complex AGV navigation challenges in confined industrial settings.