• ETRI Journal
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• v.45 no.5
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• pp.731-734
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• 2023

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.207-214
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• 2020

Currently, the operation of unmanned aerial vehicle (UAV) is regulated to be able to fly only within the visible range, but in recent years, the needs for operation in the invisible area, in the urban area and at night have increased. In order to operate UAVs in the invisible area, at night, and in the urban area, a flight path for UAVs must be prepared like those operated by manned aircraft, and for this, it is necessary to establish an unmanned aircraft system traffic management (UTM). In order to establish the UTM, information on the minimum separation distance to prevent collisions with UAVs and buildings is required, and accordingly, information on the navigation performance of UAVs is required. In order to analyze the navigation performance of an UAV, total system error (TSE), which is the difference between the planned flight path and the actual location of the UAV, is required. If the collected data are insufficient and classification according to integrity, independence, and direction is not performed, accurate navigation performance is not derived. In this paper, propose a navigation performance analysis method of UAV that is derived TSE using flight data and modeled with normal distribution, analyze performance.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.13-22
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• 2021

Among the activities of 3GPP for operating 5G-based unmanned aerial vehicles, we introduce several use cases of UAVs in 5G mobile communication such as radio access node onboard UAV, simultaneous support data transmission for UAVs and eMBB users, autonomous UAVs controlled by AI, isolated deployment of radio access through UAV, and separation of UAV service area. From this, we further summarize 5G mobile communication requirements for UAVs, including definition and operational criteria of UAS, UAS remote identification requirements, UAS usage requirements, and performance requirements. Finally, regarding 5G mobile communication-based UAS connectivity, identification and tracking support, we discuss the 3GPP UAV architecture, seven major problems, the proposed solutions to each problem, and propose the results for future specification work.

• ETRI Journal
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• v.45 no.5
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• pp.795-810
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• 2023

Unmanned aerial vehicles (UAV) and ground vehicles (UGV) require advanced video analytics for various tasks, such as moving object detection and segmentation; this has led to increasing demands for these methods. We propose a zero-shot video object segmentation method specifically designed for UAV and UGV applications that focuses on the discovery of moving objects in challenging scenarios. This method employs a background memory model that enables training from sparse annotations along the time axis, utilizing temporal modeling of the background to detect moving objects effectively. The proposed method addresses the limitations of the existing state-of-the-art methods for detecting salient objects within images, regardless of their movements. In particular, our method achieved mean J and F values of 82.7 and 81.2 on the DAVIS'16, respectively. We also conducted extensive ablation studies that highlighted the contributions of various input compositions and combinations of datasets used for training. In future developments, we will integrate the proposed method with additional systems, such as tracking and obstacle avoidance functionalities.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.622-628
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• 2016

The prosperity of IT technologies and the removal of restrictions regarding Unmanned Aerial Vehicles (UAVs), also known as drones, have driven growth in their popularity. However, without a proper solution to the problem of accident avoidance for UAVs, this popularity increases the potential for collisions between UAVs and between UAV and terrain features. These collisions can occur because UAVs to date have flown using radio control or image recognition based autonomous navigation. Therefore, we propose efficient UAV routing schemes to tackle the collision problem using vehicular communication systems. Performance evaluation by computer simulation shows that the proposed methods effectively reduce the collision probability and improve the routing efficiency of the UAV. Furthermore, the proposed algorithms are compatible and can be directly applied with small overhead to the commercial vehicular communication system implementation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.1
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• pp.38-43
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• 2022

As the use of unmanned aerial vehicles increases, in order to expand the operability of the unmanned aerial vehicle, it is essential to develop an unmanned aerial vehicle traffic management system, and to establish the system, it is necessary to analyze the integrated navigation performance of the unmanned aerial vehicle to be operated. Integrated navigation performance is affected by various factors such as the type of unmanned aerial vehicle, flight environment, and guidance law algorithm. In addition, since a large amount of flight data is required to obtain high-reliability analysis results, efficient and consistent flight scenarios are required. In this paper, a flight scenario that satisfies the requirements for integrated navigation performance analysis of rotary and fixed-wing unmanned aerial vehicles was designed and verified through flight experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.737-742
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• 2013

Recently, unmanned aircrafts for safe measurement in hazardous locations have been developed. In a method of operation of unmanned aircraft vehicles (UAV), there are two methods of manual control and automatic control. Small UAVs are used for low altitude surveillance flights where unknown obstacles can be encountered. Obstacle avoidance is one of the most challenging tasks which the UAV has to perform with high level of accuracy. In this study, we used a laser range finder as an obstacle detector in automatic navigation of unmanned aircraft to patrol the destination automatically. We proposed a system to avoid obstacles automatically by measuring the angle and distance of the obstacle using the laser range finder.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.275-275
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• 2019

기후변화에 따른 집중호우의 발생빈도와 강도가 증가하면서 대규모 홍수로 인한 인명 및 재산피해가 발생하고 있다. 그에 따라 홍수 상황을 신속하게 확보하고 홍수피해를 빠르게 예측하는 모니터링 기술이 필요하다. 최근 공간정보 분야에서 무인항공기 (UAV: Unmanned aerial vehicles)를 이용한 3차원 지형자료 확보 연구가 활발하게 이용되고 있다. 무인항공기는 지형자료 구축 뿐 만 아니라 홍수 시 신속한 홍수 모니터링이 가능하기 때문에, 본 연구에서는 무인항공기를 이용하여 홍수 전 지형자료 구축을 비롯하여, 홍수 시 모니터링, 홍수 후 지형자료 구축에 이르기까지 UAV를 이용한 홍수 모니터링 기술을 소개한다. 연구대상지는 금강 합류 직전 논산천 하류 1 km 지점으로, UAV를 이용한 지형자료를 구축하기 이전에 좌표 매칭을 위한 GCP (Ground Control Point ) 측량을 실시하고, UAV 비행계획을 수립하고 촬영한다. 촬영된 영상을 GCP좌표와 소프트웨어 (Pix4D)를 이용하여 정사영상과 DSM(Digital Surface Model)자료를 구축한다. 홍수시 UAV를 이용한 촬영을 통하여 동영상은 수재해 플랫폼에 송신하고, 이미지 영상은 홍수 전 영상처리와 동일한 방법을 이용하여 지형 자료를 구축하여, 홍수시 침수심이나 지형변화를 분석한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1941-1960
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• 2019

Unmanned aerial vehicles (UAVs), acting as mobile base stations (BSs), can be deployed in the typical fifth-generation mobile communications (5G) scenarios for the purpose of substantially enhancing the radio coverage. Meanwhile, UAV aided underlay device-to-device (D2D) communication mode can be activated for further improving the capacity of the 5G networks. However, this UAV aided D2D communication system is more vulnerable to eavesdropping attacks, resulting in security risks. In this paper, the D2D receivers work in full-duplex (FD) mode, which improves the security of the network by enabling these legitimate users to receive their useful information and transmit jamming signal to the eavesdropper simultaneously (with the same frequency band). The security communication under the UAV coverage is evaluated, showing that the system's (security) capacity can be substantially improved by taking advantage of the flexible radio coverage of UAVs. Furthermore, the closed-form expressions for the coverage probabilities are derived, showing that the cellular users (CUs)' secure coverage probability in downlink transmission is mainly impacted by the following three factors: its communication area, the relative position with UAV, and its eavesdroppers. In addition, it is observed that the D2D users or DUs' secure coverage probability is relevant to state of the UAV. The system's secure capacity can be substantially improved by adaptively changing the UAV's position as well as coverage.