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

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,...

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Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing Vol. 16; pp. 1 - 13
Main Authors: Hong, Zhonghua, Tu, Bin, Tong, Xiaohua, Pan, Haiyan, Zhou, Ruyan, Zhang, Yun, Han, Yanling, Wang, Jing, Yang, Shuhu, Ma, Zhenling
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
A star
Algorithms
Cameras
Computation
Digital Elevation Models
distributed computing
Earth
Hadoop distributed file system
hadoop distributed file system (HDFS)
Lunar exploration
Lunar roving vehicles
Methods
Moon
Parallel processing
Path planning
Planning
Random access
Remote sensing
Space missions
Spark
Sparks
Strategy
Task analysis
tile-pyramid
ISSN:1939-1404, 2151-1535
Online Access:Get full text
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Summary: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 study, 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: (1) 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; (2) 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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ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2022.3226527