• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.275-278
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• 2004

In this paper, development of the Image Transmission and Receiving System(ITRS) for UAV is being introduced. ITRS can tranfer the imagery informations from UAV to the multiple sites at the same time. Analog video signal is encoded by using MPEG4 protocol at the Image Transmission System, and the encoded digital video data can be transmitted to the various locations where the Image Receiving System decodes and displays the received video data. The ITRS might be a very efficient method of sharing UAV's information at a low cost.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1640-1651
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• 2017

To make an unmanned aerial vehicle (UAVs) fly in indoor environments, the indoor locations of the UAV are required. One of the approaches to calculate the locations of an UAV in indoor environments is enhanced trilateration using one Bluetooth-based beacon and three or more access points (APs). However, the locations of the UAV calculated by the common chord-based trilateration has errors due to the distance errors of the beacon measured at the multiple APs. This paper proposes a method that corrects the errors that occur in the process of applying the common chord-based trilateration to calculate the locations of an UAV. In the experiments, the results of measuring the locations using the proposed method in an indoor environment was compared and verified against the result of measuring the locations using the common chord-based trilateration. The proposed method improved the accuracy of location measurement by 81.2% compared to the common chord-based trilateration.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.420-428
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• 2016

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.2
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• pp.163-174
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• 2011

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.181-186
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• 2016

Recently, the surveillance system research has focused because Unmanned Aerial Vehicle(UAV) has the ability to monitor wide area. When the wide area are monitored, controlling UAVs repeatedly by pilots invokes the cost problem to operate UAVs. If monitoring path can be defined in advance, the cost problem can be solved by controlling UAVs autonomously based on the monitoring path. The traditional approach generates multiple motor primitives based on flied GPS locations. However, the monitoring points by UAVs are not considered by the generated motor primitives, the surveillance by UAVs is not performed properly. This paper proposes a motor primitive structure for surveillance UAVs to be flied autonomously. Motor primitives are generated automatically by setting surveillance points to denote surveillance targets accurately.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.197-202
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• 2014

In order to operate multiple UAVs for multiple tasks efficiently, we need a task allocation algorithm with minimum cost, i.e.,total moving distance required to accomplish the whole mission. In this paper, we have proposed the MCBAA (Modified Consensus Based Auction Algorithm) which can be suitably applied to the operation of multiple UAVs. The key idea of proposed algorithm is to minimize sum of distance from current location of agents to location of tasks based on the conventional CBAA. Several simulation test performed on three UAV agents with multiple tasks demonstrates the overall efficiency both in time and total distance.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.357-374
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• 2008

Over the past few decades, a considerable number of studies have been conducted on the technologies to build an UAV (Unmanned Aerial Vehicle) control system. Today, focus in research has moved from a standalone control system towards a network-centric control system for multiple UAV systems. Enabling the design of such complex systems in easily understandable forms that are amenable to rigorous analysis is a highly desirable goal. In this paper, we discuss our experimental evaluation of the Time-triggered Message-triggered Object (TMO) structuring scheme in the design of the UAV control system. The TMO scheme enables high-level structuring together with design-time guaranteeing of accurate timings of various critical control actions with significantly smaller efforts than those required when using lower-level structuring schemes based on direct programming of threads, UDP invocations, etc. Our system was validated by use of environment simulator developed based on an open source flight simulator named FlightGear. The TMO-structured UAV control software running on a small computing platform was easily connected to a simulator of the surroundings of the control system, i.e., the rest of the UAV and the flight environment. Positive experiences in both the TMO-structured design and the validation are discussed along with potentials for future expansion in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2666-2687
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• 2022

As a new alternative communication scheme in 5G, unmanned aerial vehicle (UAV) is used as a relay in the remote base station (BS) for assistant communication. In order to ameliorate the quality of the backhaul link, a UAV backhaul transmission scheme based on improved Nash equilibrium (NE) strategy is proposed. First, the capacity of air-to-ground (A2G) channel by the link preprocess is maximized. Then, the maximum utility function of each UAV is used as the basis of obtaining NE point according to the backhaul channel and the backhaul congestion. Finally, the improved NE strategy is applied in multiple iterations until maximum utility functions of all the UAVs are reached, and the UAVs which are rejected by air-to-air (A2A) link during the process would participate in the source recovery process to construct a multi-hop backhaul network. Simulation results show that average effective backhaul rate, minimum effective backhaul rate increases by 10%, 28.5% respectively in ideal A2G channel, and 11.8%, 42.3% respectively in fading channel, comparing to pure NE strategy. And the average number of iterations is decreased by 5%.

• Journal of Platform Technology
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• v.11 no.1
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• pp.3-10
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• 2023

Unmanned Aerial Vehicles (UAVs) have gained significant attention in 5G and 6G wireless networks due to their high flexibility and low hardware costs. However, UAV communication is still challenged by blockage and energy consumption issues. Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising solution to these challenges, enabling improved spectral efficiency and reduced energy consumption by transmitting signals to users who cannot receive signals because of the obstacles. Many previous studies have focused on minimizing power consumption and data transmission delay through phase shift and power optimization. This paper proposes an algorithm that maximizes the sum rate by including bandwidth optimization. Simulation results demonstrate the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.