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Improved A* Algorithm for Mobile Robots under Rough Terrain Based on Ground Trafficability Model and Ground

Zhiguang Liu¹, Song Guo^2,3, Fei Yu^2,3

¹School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin 300384, China.

Sensors (Basel, Switzerland)

|August 10, 2024

Summary

This study introduces an improved A* algorithm for mobile robot path planning in rugged terrain. The enhanced algorithm ensures smoother, more optimal paths, preventing center-of-mass instability.

Keywords:

A* algorithm elevation maps path planning rough terrain

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Area of Science:

Robotics
Artificial Intelligence
Computer Science

Background:

Existing path planning algorithms for rugged terrain lack ground flatness consideration, leading to mobile robot instability.
Mobile robot path planning in uneven environments requires algorithms that ensure stability and optimality.

Purpose of the Study:

To propose an improved A* algorithm for mobile robot path planning in rugged terrain.
To enhance path smoothness and optimality, thereby preventing center-of-mass instability.

Main Methods:

Developed ground accessibility and ruggedness models based on elevation maps to quantify ground flatness.
Designed an elevation cost function integrated with the A* algorithm and original distance cost function.
Validated the improved algorithm through simulations and experimental testing.

Main Results:

The improved A* algorithm generates smoother paths compared to existing methods.
The algorithm achieves a higher degree of path optimization for mobile robots on rough terrain.
Demonstrated reduction in center-of-mass instability through enhanced path planning.

Conclusions:

The proposed improved A* algorithm effectively addresses the limitations of existing path planning methods for rugged terrain.
The algorithm enhances both path smoothness and optimality, crucial for mobile robot stability.
The ground accessibility and ruggedness models provide a robust foundation for optimal path generation.