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Lookup NU author(s): Dr Pooya SarehORCiD
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© 2026 Institution of Structural Engineers. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. 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.
Author(s): Shao Z, Chen Y, Li Y, Xie T, Feng J, Sareh P
Publication type: Article
Publication status: Published
Journal: Structures
Year: 2026
Volume: 88
Print publication date: 01/06/2026
Online publication date: 23/04/2026
Acceptance date: 20/04/2026
ISSN (electronic): 2352-0124
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.istruc.2026.111927
DOI: 10.1016/j.istruc.2026.111927
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