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Cited by 12Robotic Path Planning AlgorithmsPlanetary Science and ExplorationReinforcement Learning in Robotics

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

A Fast Large-Scale Path Planning Method on Lunar DEM Using Distributed Tile Pyramid Strategy

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Hong, Zhonghua, Tu, Bin, Tong, Xiaohua, Pan, Haiyan, Zhou, Ruyan, Zhang, Yun, Han, Yanling, Wang, Jing, Yang, Shuhu, Ma, Zhenling·2023·IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
DOI 10.1109/jstars.2022.3226527
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Abstract

In lunar exploration missions, path planning for lunar rovers using digital elevation models (DEMs) is currently a hot topic in academic research. However, research on path planning using large-scale DEMs has rarely been discussed, owing to the low time efficiency of existing algorithms. Therefore, in this article, we propose a fast path-planning method using a distributed tile pyramid strategy and an improved A*algorithm. The proposed method consists of three main steps. First, the tile pyramid is generated for the large lunar DEM and stored in Hadoop distributed file system. Second, a distributed path-planning strategy based on tile pyramid (DPPS-TP) is used to accelerate path-planning tasks on large-scale lunar DEMs using Spark and Hadoop. Finally, an improved A*algorithm was proposed to improve the speed of the path-planning task in each tile. The method was tested using lunar DEM images. Experimental results demonstrate that: in a single-machine serial strategy using source DEM generated by the Chang'e-2 CCD stereo camera, the proposed A*algorithm for open list and closed list with random access feature (OC-RA-A*algorithm) is 3.59 times faster than the traditional A*algorithm in long-distance path planning tasks and compared to the distributed parallel computation strategy using source DEM generated by the Chang'e-2 CCD stereo camera, the proposed DPPS-TP based on tile pyramid DEM is 113.66 times faster in the long-range path planning task.

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  • Hong et al. proposed a fast path-planning method using a distributed tile pyramid strategy and an improved A* algorithm.

    “Hong et al. proposed a fast path-planning method using a distributed tile pyramid strategy and an improved A * algorithm. 226”

    From Energy system and resource utilization in space: A state-of-the-art review (2024) · cites this paper as [226]

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  1. marlina, 2017, Penerapan algoritma Dijkstra dan Floyd-Warshall untuk Menentukan rute Terpendek Tempat Wisata di Batang, UNNES J Math, 6, 36

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Metadata

Authors
Hong, Z., Tu, B., Tong, X., Pan, H., Zhou, R., Zhang, Y., Han, Y., Wang, J., Yang, S., & Ma, Z.
Affiliations
  • Shanghai Ocean University (CN)
  • Tongji University (CN)
ORCID
Venue
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2023
Volume
16
Pages
344-355
ISSN
  • 1939-1404 (ISSN-L)
  • 2151-1535
DOI
10.1109/jstars.2022.3226527
OpenAlex
W4312051513
Cited by
12
References
34
Citations by year
2026: 2 · 2025: 3 · 2024: 3 · 2023: 4
FWCI
0.82
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Key R&D Program of China (2018YFB0505400)
  • National Natural Science Foundation of China (41871325)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
  • Physical Sciences › Earth and Planetary Sciences › Space and Planetary Science › Planetary Science and Exploration
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
Keywords
lunar digital elevation model, distributed computing, improved A* algorithm, Hadoop, Spark

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