HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE

Computerized path planning, not constrained to transportation networks, may be useful in a range of settings, from search and rescue to archaeology. This paper develops a method for general path planning intended to work across arbitrary distances and at the level of terrain detail afforded by aeria...

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Main Authors: K. Landmark, E. Messel
Format: Article
Language:English
Published: Copernicus Publications 2018-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W8/109/2018/isprs-archives-XLII-4-W8-109-2018.pdf
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spelling doaj-b3ff9e90c17f4e1baf238f1076bc856f2020-11-25T00:21:38ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-07-01XLII-4-W810911610.5194/isprs-archives-XLII-4-W8-109-2018HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHEREK. Landmark0E. Messel1Norwegian Defence Research Establishment (FFI), P.O. Box 25, 2027 Kjeller, NorwayNorwegian Defence Research Establishment (FFI), P.O. Box 25, 2027 Kjeller, NorwayComputerized path planning, not constrained to transportation networks, may be useful in a range of settings, from search and rescue to archaeology. This paper develops a method for general path planning intended to work across arbitrary distances and at the level of terrain detail afforded by aerial LiDAR scanning. Relevant information about terrain, trails, roads, and other infrastructure is encoded in a large directed graph. This basal graph is partitioned into strongly connected subgraphs such that the generalized diameter of each subgraphs is constrained by a set value, and with nominally as few subgraphs as possible. This is accomplished using the k-center algorithm adapted with heuristics suitable for large spatial graphs. A simplified graph results, with reduced (but known) position accuracy and complexity. Using a hierarchy of simplified graphs adapted to different length scales, and with careful selection of levels in the hierarchy based on geodesic distance, a shortest path search can be restricted to a small subset of the basal graph. The method is formulated using matrix-graph duality, suitable for linear algebra-oriented software. Extensive use is also made of public data, including LiDAR, as well as free and open software for geospatial data processing.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W8/109/2018/isprs-archives-XLII-4-W8-109-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. Landmark
E. Messel
spellingShingle K. Landmark
E. Messel
HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet K. Landmark
E. Messel
author_sort K. Landmark
title HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
title_short HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
title_full HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
title_fullStr HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
title_full_unstemmed HIERARCHICAL PATH PLANNING FOR WALKING (ALMOST) ANYWHERE
title_sort hierarchical path planning for walking (almost) anywhere
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2018-07-01
description Computerized path planning, not constrained to transportation networks, may be useful in a range of settings, from search and rescue to archaeology. This paper develops a method for general path planning intended to work across arbitrary distances and at the level of terrain detail afforded by aerial LiDAR scanning. Relevant information about terrain, trails, roads, and other infrastructure is encoded in a large directed graph. This basal graph is partitioned into strongly connected subgraphs such that the generalized diameter of each subgraphs is constrained by a set value, and with nominally as few subgraphs as possible. This is accomplished using the k-center algorithm adapted with heuristics suitable for large spatial graphs. A simplified graph results, with reduced (but known) position accuracy and complexity. Using a hierarchy of simplified graphs adapted to different length scales, and with careful selection of levels in the hierarchy based on geodesic distance, a shortest path search can be restricted to a small subset of the basal graph. The method is formulated using matrix-graph duality, suitable for linear algebra-oriented software. Extensive use is also made of public data, including LiDAR, as well as free and open software for geospatial data processing.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W8/109/2018/isprs-archives-XLII-4-W8-109-2018.pdf
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