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7 December 2023 Research on improved Astar algorithm based on domain expansion strategy
Wei Sun, Yu Chen, Dong Zhang, Shuai Cheng, Li Li
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Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294109 (2023) https://doi.org/10.1117/12.3011975
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
This paper proposes an improved Astar algorithm based on domain expansion strategy to address the problem of traditional Astar algorithms that plan paths that are not globally optimal and have large path lengths. Specifically, expanding the traditional Astar algorithm's eight search domains to 24 domains, increasing the search scope; optimizing the heuristic function by using a dynamic weight heuristic function instead of the traditional one. In order to verify the effectiveness of the improved Astar algorithm, simulation experiments were conducted on both the traditional Astar algorithm and the improved Astar algorithms in the same environment. The simulation results show that compared to the traditional Astar algorithm, the improved Astar algorithm based on domain expansion strategy planned has a shorter planned path, lower total path cost, and better overall search performance.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Wei Sun, Yu Chen, Dong Zhang, Shuai Cheng, and Li Li "Research on improved Astar algorithm based on domain expansion strategy", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294109 (7 December 2023); https://doi.org/10.1117/12.3011975
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KEYWORDS
Detection and tracking algorithms
Computer simulations
Mathematical optimization
Mobile robots
Raster graphics
Transportation
Unmanned vehicles
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