UGVs’ Navigation Supported by Multi-UAVs in a ROS Environment

It is challenging for unmanned ground vehicles (UGVs) to navigate in an unknown environment without equipping them with sensors, such as LiDAR, cameras, etc. As a result, it is necessary to employ an unmanned aerial vehicle (UAV) to provide the UGVs with map information, obstacle information and relative position estimations. The UGVs receive the messages from the UAV and then automatically plan a global route. When approaching obstacles, UGVs release collision position messages to the UAV. This UAV calculates the optimal path point based on the collision position and the time to collision of the UGVs. However, the UAV’s relative position estimation equipment has a limited range, such that it cannot provide all UGVs with the information in time. This means that UGVs receive information late or even lose communication with the UAV. To address the above issues, this paper advocates for the use of multiple UAVs and the creation of different communication strategies. A variety of tests are conducted in a simulated environment built in ROS to pair each UAV with different numbers of UGVs and explore their initial positions to find the most suitable configuration.

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Publication Details

Journal
Electronics
Published
2024-11-28
DOI
https://doi.org/10.3390/electronics13234708
Citations
2
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
2.60

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article

UGVs’ Navigation Supported by Multi-UAVs in a ROS Environment

Xiaoyu Bi, Jian Song, Tingting Yang, Yiyang Chen et al.
2 citations
Electronics
Robotics and Sensor-Based Localization
2.60
article

UGVs’ Navigation Supported by Multi-UAVs in a ROS Environment

Xiaoyu Bi, Jian Song, Tingting Yang, Yiyang Chen, Xinlin Li, Yixin Shi
article en
2 citations

Abstract

It is challenging for unmanned ground vehicles (UGVs) to navigate in an unknown environment without equipping them with sensors, such as LiDAR, cameras, etc. As a result, it is necessary to employ an unmanned aerial vehicle (UAV) to provide the UGVs with map information, obstacle information and relative position estimations. The UGVs receive the messages from the UAV and then automatically plan a global route. When approaching obstacles, UGVs release collision position messages to the UAV. This UAV calculates the optimal path point based on the collision position and the time to collision of the UGVs. However, the UAV’s relative position estimation equipment has a limited range, such that it cannot provide all UGVs with the information in time. This means that UGVs receive information late or even lose communication with the UAV. To address the above issues, this paper advocates for the use of multiple UAVs and the creation of different communication strategies. A variety of tests are conducted in a simulated environment built in ROS to pair each UAV with different numbers of UGVs and explore their initial positions to find the most suitable configuration.

ElectronicsVol. 13(23)
Civil Aviation University of China (CN), UNSW Sydney (AU), Soochow University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 8%
Robotics and Sensor-Based Localization
2.60
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UGVs’ Navigation Supported by Multi-UAVs in a ROS Environment — Xiaoyu Bi, Jian Song, et al. · Electronics (2024) | TGRS Research Map | TGRS