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JACIII Vol.27 No.4 pp. 664-672
doi: 10.20965/jaciii.2023.p0664
(2023)

Research Paper:

Joint Path and Multi-Hop Communication Node Location Planning in Cluttered Environment

Lihua Li*, Zhihong Peng*,†, Chengxin Wen*, Peiqiao Shang*, and Jinqiang Cui**

*School of Automation, Beijing Institute of Technology
5 South Street, Zhongguancun, Haidian District, Beijing 100081, China

Corresponding author

**Department of Mathematics and Theories, Peng Cheng Laboratory
2 Xingke 1st Street, Nanshan, Shenzhen 518055, China

Received:
January 1, 2023
Accepted:
April 4, 2023
Published:
July 20, 2023
Keywords:
UAV, multi-hop communication, rescue scenario, path planning
Abstract

In the communication-constrained operating environment, a unmanned aerial vehicle (UAV) needs to plan a feasible path from the starting point to the endpoint while planning the node deployment location for multi-hop communication to establish an information pathway. In this study, a new algorithm was designed for joint path and multi-hop communication node location planning in cluttered environments based on rapidly-exploring random trees star (RRT*) algorithm. The maximum communication distance constraint between nodes was obtained based on the signal-free propagation model, whereas the communication node loss and path loss were established as joint optimization objectives. In bidirectional random tree growth, the structure of the trees was optimized according to the value of the loss function, and optimal path and node location planning were finally achieved through continuous growth and iteration. When tested in different complexity-barrier environments and compared to RRT*, Informed-RRT*, and IB-RRT* algorithms, the paths in the planning results of the new algorithm are close to those of the comparison algorithms; however, the number of nodes decreases significantly, which proves the effectiveness of the newly proposed algorithm.

Cite this article as:
L. Li, Z. Peng, C. Wen, P. Shang, and J. Cui, “Joint Path and Multi-Hop Communication Node Location Planning in Cluttered Environment,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.4, pp. 664-672, 2023.
Data files:
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