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JACIII Vol.28 No.3 pp. 475-483
doi: 10.20965/jaciii.2024.p0475
(2024)

Research Paper:

Research on the Messenger UAV Mission Planning Based on Sampling Transformation Algorithm

Benxiang Wang*, Bin Xin*,†, Yulong Ding**, and Yang Li***

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

Corresponding author

**Peng Cheng Laboratory
Shibi Long Park Phase I, Shenzhen 518000, China

***Beijing Institute of Electronic Engineering
Yongding Road, Haidian District, Beijing 102206, China

Received:
March 17, 2023
Accepted:
August 4, 2023
Published:
May 20, 2024
Keywords:
urban environment, path planning, messenger mechanism, TSP
Abstract

In recent years, there has been a significant development in unmanned platform technologies, specifically unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). As a result, their application scenarios have expanded considerably. Unmanned platforms are considered integral components of the Internet of Things system. However, certain challenges arise when dealing with specialized tasks, such as navigating complex urban low-altitude terrain with multiple obstacles and limited communication capabilities. These challenges can greatly impact the efficiency of the system due to information isolation. To address this issue, a messenger drone mechanism is introduced in this paper, which utilizes air superiority to facilitate indirect communication between unmanned platforms. Additionally, a task sequence planning algorithm based on sampling transformation is designed. This algorithm efficiently assigns the drone to mobile UGVs by discretely sampling their paths and considering the UAV-UGV motion relationship. By transforming the problem into an asymmetric traveler problem, it allows for a fast solution. Finally, the effectiveness of the algorithm is verified through comparative analysis in different scenarios.

Cite this article as:
B. Wang, B. Xin, Y. Ding, and Y. Li, “Research on the Messenger UAV Mission Planning Based on Sampling Transformation Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.3, pp. 475-483, 2024.
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Last updated on Jul. 12, 2024