Energy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm

Moon, SungTae; Lee, Donghun; Lee, Dongoo; Kim, Doyoon; Bang, Hyochoong

doi:10.3390/s21041260

Cited by 8 publications

(7 citation statements)

References 40 publications

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“…However, in the case of outdoor swarm flight, GNSS sensors are insufficient because position accuracy within 1 m is required to avoid collisions between drones. Moon et al [6] proposed an RTK-GPS-based position estimation algorithm to improve position accuracy and built a system that allows hundreds of drones to operate within 1 m of each other without colliding.…”

Section: A Uav Swarmmentioning

confidence: 99%

“…Additionally, robust communication is required for stable swarm flight. Moon et al [6] proposed a passive approach that minimizes the amount of communication by inputting the missions to the drones in advance for stable communication with hundreds of drones. However, the passive approach is not suitable for a swarm reconnaissance system because performing a dynamic mission is difficult.…”

Section: A Uav Swarmmentioning

confidence: 99%

“…However, since verification was performed through simulations, verification in a real environment is necessary. Moon et al [6] used the Fair Hungarian method considering the battery condition to ensure that the battery consumption of the drones was even and verified their approach with 100 drones. However, this method is not suitable for a swarm reconnaissance drone system because performing a dynamic mission is difficult due to the passive mission approach.…”

Section: A Uav Swarmmentioning

confidence: 99%

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Swarm Reconnaissance Drone System for Real-Time Object Detection Over a Large Area

et al. 2023

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Recent developments in drone technology have led to the widespread use of unmanned aerial vehicles (UAVs). In particular, UAVs are often used in reconnaissance to detect objects such as missing persons in large areas. However, traditional systems use only one UAV to search for missing persons in a large area. In addition, object detection is performed after flight or manually because detection requires high computing power. In this paper, a reconnaissance drone system using multiple UAVs is proposed. The proposed multi-UAV reconnaissance system performs real-time object detection on each UAV. The realtime object detection results from each UAV are received by the ground control system (GCS) to stitch the images. To enable real-time object detection in individual UAVs, the filter pruning method is applied to the YOLOv5 model, and the model uses 40% fewer parameters than the existing baseline model. The lightweight YOLOv5 model achieves approximately 11.73 FPS on the Jetson Xaiver NX using a mission computer. Moreover, the proposed image stitching method enables image stitching by effectively matching features using additional information generated by UAVs. The UAV flight tests show that the proposed reconnaissance system can monitor and detect objects in real time over large areas.INDEX TERMS Image stitching, network pruning, real-time object detection, swarm flight system.

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Section: A Uav Swarmmentioning

confidence: 99%

Section: A Uav Swarmmentioning

confidence: 99%

Section: A Uav Swarmmentioning

confidence: 99%

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Swarm Reconnaissance Drone System for Real-Time Object Detection Over a Large Area

et al. 2023

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“…When sizing the network for smart metering, it is necessary to strategically consider deploying wireless networks to generate efficient and reliable bidirectional communication between consumers and service providers [14]. This article analyzes only neighborhood area network (NAN) deployment with channel reuse [15,16].…”

Section: Related Workmentioning

confidence: 99%

Maximizing Resource Efficiency in Wireless Networks through Virtualization and Opportunistic Channel Allocation

Inga

Hincapié

2023

Sensors

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Wireless cellular networks have become increasingly important in providing data access to cellular users via a grid of cells. Many applications are considered to read data from smart meters for potable water, gas, or electricity. This paper proposes a novel algorithm to assign paired channels for intelligent metering through wireless connectivity, which is particularly relevant due to the commercial advantages that a virtual operator currently provides. The algorithm considers the behavior of secondary spectrum channels assigned to smart metering in a cellular network. It explores spectrum reuse in a virtual mobile operator to optimize dynamic channel assignment. The proposed algorithm exploits the white holes in the cognitive radio spectrum and considers the coexistence of different uplink channels, resulting in improved efficiency and reliability for smart metering. The work also defines the average user transmission throughput and total smart meter cell throughput as metrics to measure performance, providing insights into the effects of the chosen values on the overall performance of the proposed algorithm.

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“…The proposed system can control multiple UAVs simultaneously to find the location of a UWB tag. Recently, the Korea Aerospace Research Institute (KARI) developed a swarming flight system that can operate with an arbitrary number of UAVs [26]. This system was used in a drone show in which multiple UAVs were precisely controlled using RTK-GPS, as shown in Fig.…”

Section: Proposed Movable Uwb Anchor System Based On a Swarm Of Uavsmentioning

confidence: 99%

A Novel Movable UWB Localization System Using UAVs

Moon

Youn

2022

IEEE Access

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Recently, interest in ultrawideband (UWB)-based localization systems has increased in various application fields. However, since UWB anchors are usually fixed, they work only within the limited range that UWB measurement signals can reach. To address this issue, a swarm flight system with movable UWB anchors is developed. One ground station controls multiple unmanned aerial vehicles (UAVs), each of which is equipped with a UWB anchor and real-time kinematic global positioning system (RTK-GPS) capabilities, and collects the precise (centimeter-level) positions of the UWB anchor UAVs through RTK-GPS. In this way, the constraints of existing UWB systems can be alleviated by changing the UWB anchor positions in real time as desired by the user. In addition, this paper proposes a novel localization algorithm using only time-of-flight (TOF) measurements from UWB signals, heading information from an attitude and heading reference system (AHRS), and altitude information from a barometer. The results of UAV flight tests show that the proposed algorithm provides better localization performance than existing algorithms.INDEX TERMS Interacting multiple model, Kalman filter, localization, swarm flight system, ultrawideband (UWB), unmanned aerial vehicle (UAV).

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Energy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm

Cited by 8 publications

References 40 publications

Swarm Reconnaissance Drone System for Real-Time Object Detection Over a Large Area

Swarm Reconnaissance Drone System for Real-Time Object Detection Over a Large Area

Maximizing Resource Efficiency in Wireless Networks through Virtualization and Opportunistic Channel Allocation

A Novel Movable UWB Localization System Using UAVs

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