The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Geometric A-Star Algorithm: An Improved A-Star Algorithm for AGV Path Planning in a Port Environment
Open accessAbstract
This research introduces a path planning method based on the geometric A-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions P(x,y ) and W(x,y ) and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric A-star algorithm reduces the number of nodes by 10% ~ 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric A-star algorithm.
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Cites
A Formal Basis for the Heuristic Determination of Minimum Cost Paths
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Path Planning with Modified a Star Algorithm for a Mobile Robot
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Heuristic approaches in robot path planning: A survey
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An improved ant colony algorithm for robot path planning
Liu, J., Yang, J., Liu, H., Tian, X., & Gao, M. (2017) · Soft Computing · doi:10.1007/s00500-016-2161-7 · Cited by 396
Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges
Ravankar, A., Ravankar, A. A., Kobayashi, Y., Hoshino, Y., & Peng, C.-C. (2018) · Sensors · doi:10.3390/s18093170 · Cited by 314
Smoothed A* algorithm for practical unmanned surface vehicle path planning
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Surface Optimal Path Planning Using an Extended Dijkstra Algorithm
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Cited by
A Fast Large-Scale Path Planning Method on Lunar DEM Using Distributed Tile Pyramid Strategy
Hong, Z., Tu, B., Tong, X., Pan, H., Zhou, R., Zhang, Y., Han, Y., Wang, J., Yang, S., & Ma, Z. (2023) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3226527 · Cited by 12
Metadata
- Authors
- Tang, G., Tang, C., Claramunt, C., Hu, X., & Zhou, P.
- Venue
- IEEE Access
- Published
- 2021
- Volume
- 9
- Pages
- 59196-59210
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3140133525
- Cited by
- 474
- References
- 19
- FWCI
- 24.78
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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