Path-Planning on a Spherical Surface with Disturbances and Exclusion Zones

An algorithm is presented for path-planning in a non-uniform spheroid mesh containing exclusion zones, vector and scalar fields. The mesh models physical environments such as ocean regions, together with a variety of environmental phenomena such as wind, current and ice conditions which impact on routing decisions. The path-planning method can be used to optimise the travel time of journeys between points in the mesh. We provide the algorithmic details and the mathematical foundations of the algorithms. To demonstrate that the method has basic desirable properties, we show that long paths in unconstrained regions of the mesh closely approximate great circle arcs. We go on to show that the method path-plans efficiently in environments with complex interacting conditions.

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Publication Details

Journal
Journal of Artificial Intelligence Research
Published
2025-03-28
DOI
https://doi.org/10.1613/jair.1.16746
Citations
1
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
1.15
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article

Path-Planning on a Spherical Surface with Disturbances and Exclusion Zones

Derek Long, Maria Fox, Jonathan Smith, G. Coombs et al.
1 citations
Journal of Artificial Intelligence Research
Evacuation and Crowd Dynamics
1.15
article

Path-Planning on a Spherical Surface with Disturbances and Exclusion Zones

Derek Long, Maria Fox, Jonathan Smith, G. Coombs, S. Hall, Michael Thorne, Harrison Abbot, Ayat Fekry
article en
1 citations

Abstract

An algorithm is presented for path-planning in a non-uniform spheroid mesh containing exclusion zones, vector and scalar fields. The mesh models physical environments such as ocean regions, together with a variety of environmental phenomena such as wind, current and ice conditions which impact on routing decisions. The path-planning method can be used to optimise the travel time of journeys between points in the mesh. We provide the algorithmic details and the mathematical foundations of the algorithms. To demonstrate that the method has basic desirable properties, we show that long paths in unconstrained regions of the mesh closely approximate great circle arcs. We go on to show that the method path-plans efficiently in environments with complex interacting conditions.

Journal of Artificial Intelligence ResearchVol. 82
British Antarctic Survey (GB), King's College London (GB)
Openalex Percentile: Top 25%
Evacuation and Crowd Dynamics
1.15
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Path-Planning on a Spherical Surface with Disturbances and Exclusion Zones — Derek Long, Maria Fox, et al. · Journal of Artificial Intelligence Research (2025) | TGRS Research Map | TGRS