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Robotic construction in multi-surface environments: Friction-adaptive path planning using an improved A* algorithm
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AI
DOI：10.1016/j.istruc.2026.111927.png)
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Abstract
En 中文
In recent years, growing concerns about the challenging conditions in construction and the significant environmental impact of construction activities have increased the focus on intelligent construction solutions. Construction robotics has emerged as a major focus within the field of intelligent construction. However, mobile robots continue to face challenges during construction processes, including large work areas, numerous obstacles, and varying ground friction conditions. To address these challenges, we proposed an improved A* algorithm for path planning, incorporating the effects of varying ground friction conditions across the map. First, the path-planning performances of the A*, PRM, and ant colony algorithms on a large-scale map were analyzed and compared. The results demonstrated that the A* algorithm exhibited the highest computational efficiency and achieved the most optimized path length. Building on these findings, an improved A* algorithm was developed to optimize path length and reduce the number of turning points. A path-planning method tailored to maps with varying ground friction conditions was further designed. Finally, examples featuring maps of different scales and ground friction characteristics were employed to validate the effectiveness of the proposed path-planning method in real construction environments.
Keywords:
Construction robotics
Path planning
A* algorithm
Ground friction
Intelligent construction
Journal
IF:
4.3
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1.2W
Citations:
2.7W