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Swarm Reconnaissance Drone System for Efficient Object Detection
SungTae Moon, Jihoon Jeon, Yongwoo Kim
http://doi.org/10.5626/JOK.2022.49.9.715
With the recent development in drone technology, drones are being used in numerous industries such as cultural performances, logistics delivery, and traffic monitoring. In particular, as drones are used in reconnaissance fields such as the search for missing people and intruder detection, efficient mission performance has become possible. For effective reconnaissance, it is necessary to quickly monitor a large area and find a target in real-time. However, the current system cannot obtain real-time reconnaissance results because it is difficult to process inside the drone due to its performance limitations. In addition, it is difficult to conduct integrated commands and share information because it is judged based on the images obtained individually from the drone. This paper proposes a pruning algorithm and active swarm reconnaissance system for object detection based on stitched drone images. Using four drones, the proposed system verifies the real-time object detection and swarm operation system.
Feature Pyramid Network-based Long-Distance Drone Detection Method
Jeongin Kwon, Sohee Son, Jinwoo Jeon, Injae Lee, Jihun Cha, Haechul Choi
http://doi.org/10.5626/JOK.2021.48.3.325
With the rapid development in the field of drones, the need for a surveillance system to prevent accidents caused by drones has increased. Considering the high speed of drones, they must be detected from a distance. In long-distance images, the target size is very small and the background can be complex. Even if a deep learning technique is used for object detection the false detection rate remains very high. This paper introduces a multi-frame based post-processing method that can effectively reduce the false detection rate of feature pyramid network (FPN), which works well for tiny-object detection. The proposed post-processing method indexes detected objects and compares the distance and size difference concerning the corresponding objects of the previous frame to determine whether it is a false positive (FP) or not. FPN is trained on 44,986 images with annotations from 360 image sequences taken by hand. Experimental results show that the proposed method reduces the FP rate overall evaluation sequences by more than 80% and also increases the F-measure.
Outdoor Swarm Flight System Based on the RTK-GPS
SungTae Moon, DoYoon Kim, DonGoo Lee
http://doi.org/10.5626/JOK.2020.47.3.328
The increasing interest in drones has generated new application systems in the various areas. Especially, the drone-show performance applying the swarm flight system impressed many people globally at the Pyeongchang Winter Olympics. However, this technology is Intel technology, not domestic proprietary technology. Thus, the KARI (Korean Aerospace Research Institute) has developed the swarm flight system based on the RTK-GPS and verified the system by showing the 100 drone-show at the independence movement day. In this paper, the propose a robust swarm flight system which can switch the mode according to the RTK-GPS condition. The efficient precise position estimation, communication system, and how to develop the scenario are explained.
An Offloading Scheme for Reliable Data Processing of Swarm-drones
Hong Min, Bongjae Kim, Junyoung Heo, Jinman Jung
http://doi.org/10.5626/JOK.2018.45.10.990
With the developing drone-related technologies, autonomous drones have many applications. The offloading technique is used to execute high computational tasks that are stored in the cloud to preserve the limited resources of a drone. In this paper, we determine the effect of offloading by using cost analysis for swarm-drones considering task completion time and energy consumption. If the drones take more time and spend more energy while offloading their tasks to the cloud, drones divide a large task into small tasks. These tasks are run by using the drone’s own resources to process data reliably and efficiently. Our simulation results also show how the task completion time and the energy consumption infuence the offloading decision.
Implementation of Intra-Partition Communication in Layered ARINC 653 for Drone Flight-Control Program
Joo-Kwang Park, Jooho Kim, Hyun-Chul Jo, Hyun-Wook Jin
http://doi.org/10.5626/JOK.2017.44.7.649
As the type and purpose of drones become diverse and the number of additional functions is increasing, the role of the corresponding software has increased. Through partitioning and an efficient solving of SWaP(size, weight and power) problems, ARINC 653 can provide reliable software reuse and consolidation regarding avionic systems. ARINC 653 can be more effectively applied to drones, a small unmanned aerial vehicle, in addition to its application with large-scale aircraft. In this paper, to exploit ARINC 653 for a drone flight-control program, an intra-partition communication system is implemented through an extension of the layered ARINC 653 and applied to a real drone system. The experiment results show that the overheads of the intra-partition communication are low, while the resources that are assigned to the drone flight-control program are guaranteed through the partitioning.
Development of a Motor Speed Controller of Drones Considering Voltage Drop of Battery
Sunghee Lee, Bo Ram Yun, Deok Yeop Kim, Hwangsoo Kim, Woo Jin Lee
http://doi.org/10.5626/JOK.2017.44.6.601
Recently, we have frequently encountered flying drones with the growth of drone industry. However, it is difficult for a driver to stabilize the motor speed of drones, since the voltage of a Lithium polymer battery used in drones may suddenly drop or rise when its power is exhausted. The instability of the motor speed precludes the drone from maintaining a flight altitude, so that the fuselage of a drone performs ascending and descending repeatedly. For solving this problem, existing techniques either add a compensator considering voltage drop of battery or change the control model. Since these techniques use hardware-implemented modules or depend on motor type and experimental results, there is a problem that new suitable modules should be implemented in accordance with the used motor of the fuselage. For solving this problem, in this paper, we implement a motor speed controller in the firmware of drones by considering voltage drop of battery to enhance drone flight stability.
Outdoor Swarm Flight System Based on RTK-GPS
SungTae Moon, YeonJu Choi, DoYoon Kim, Myeonghun Seung, HyeonCheol Gong
Recently, the increasing interest in drones has resulted in development of new related technologies. Attention has been focused toward research on swarm flight which controls drones simultaneously without collision. Thus, complicated missions can be completed rapidly through collaboration between drones. Due to low position accuracy, GPS is not appropriate for the outdoor mission involving accurate flight. In addition, the inaccurate position estimation of GPS gives rise to the serious problem of collision, since many drones are controlled in a narrow space. In this study, we increased the accuracy of position estimation through various sensors with Real-Time Kinematic-GPS (RTK-GPS). The mode switching algorithm was proposed to minimize the problem of sensor error. In addition, we introduced the outdoor swarm flight system based on the proposed position estimation.
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