• Aerospace Engineering and Technology
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• v.5 no.2
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• pp.1-7
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• 2006

This paper presents a new point navigation guidance law which is useful for unmanned helicopters. Predicting the future position, the guidance law generates velocity and heading commands, which are used as input to autopilot. This method differs from conventional guidance law in that it reorients the direction of flight velocity vector directly, not by bank angle indirectly. For flight tests, we have developed a flight control system for a R/C helicopters. The system consists of a flight control computer, navigation sensors, and a ground station The results of the test show that the proposed law guides a unmanned helicopter along a line path within a given area. In the future, we are planning to extend the guidance law to the mission of path following. i.e., waypoint navigation.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.94-106
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• 2017

Unmanned military vehicles (UMVs) will be increasingly applied to the various military operations. These UMVs are most commonly characterized as dealing with "4D" task - dull, dirty, dangerous and difficult with automations. Although most of the UMVs are designed to a high degree of autonomy, the human operator will still intervene in the robots operation, and tele-operate them to achieve his or her mission. Thus, operator capacity, along with robot autonomy and user interface, is one of the important design factors in the research and development of the UMVs. In this paper, we propose the method to assess the operator capacity of the UMVs. The method is comprised of the 6 steps (problem, assumption, goal function identification, operator task analysis, task modeling & simulation, results and assessment), and herein colored Petri-nets are used for the modeling and simulation. Further, an illustrative example is described at the end of this paper.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.13-18
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• 2018

Drones are controlled by the remote pilot from the ground stations using the radio control or autonomously following the pre-programmed flight plans. In this paper, we develop a method and an optimal path search system for providing 3D augmented reality flight (ARF) images for safe and efficient flight control of drones. The developed system consisted of the drone, the ground station and user terminals, and the optimal path search server. We use the Dijkstra algorithm to find the optimal path considering the drone information, flight information, environmental information, and flight mission. We generate a 3D augmented reality flight (ARF) image overlaid with the path information as well as the drone information and the flight information on the flight image received from the drone. The ARF image for adjusting the drone is generated by overlaying route information, drone information, flight information, and the like on the image captured by the drone.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.529-536
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• 2017

The general ground control system has control and information display functions for the operation of a single unmanned aerial vehicle. Recently, the function of the single ground control system extends to the operation of multiple UAVs. As a result, operators have been exposed to more diverse tasks and are subject to task overload due to various factors during their mission. This study proposes an adaptive ground control system that reflects the operator's condition through the task overload measurement of multiple UAV operators. For this, the ground control software is developed to control multiple UAVs at the same time, and the simulator with six degree-of-freedom aircraft dynamics is constructed for realistic human-machine-interface experiments by the operators.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.3
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• pp.212-219
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• 2019

As unmanned aerial vehicle (UAV) has been utilized for military operation, efficient ways for controlling UAV has been necessary. In particular, instead of conventional approach using console control, speech recognition based UAV control is essential for military environments in which rapid command operation is required. But research on this novel approach is not actively studied yet. In this study, we introduce efficient ways of speech recognition system operation for voice-driven UAV control, focusing on mission command control from manned aircraft rather than ground control center. We propose an efficient way of system operation for UAV control in cooperation of aircraft and UAV, and verify its efficiency via speech recognition experiment.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.68-76
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• 2021

The series hybrid system targeted in this study uses a reciprocating engine, a generator, and a battery as a main power source for the unmanned aerial vehicle. The generator is directly connected to the drive shaft of the reciprocating engine, and the operating characteristics of the reciprocating engine-generator set were confirmed through ground integration tests. In this study, based on the test results, a control logic is proposed an efficient use of the reciprocating engine-generator power and battery power. Also, the power variations of the reciprocating engine-generator and battery according to the logic were verified through simulation. As a result, it was confirmed that the engine-generator power supplied the power required for propulsion along with the battery power by the proposed control logic.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.182.1-182.1
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• 2005

• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.520-523
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• 2012

본 연구에서 무인차량의 자율주행시스템은 차량제어시스템, 항법시스템, 장애물인식시스템, 통합시스템의 4개 서브시스템으로 구성 되어있고, GPS와 레이저스캐너를 이용한 무인차량의 장애물인식시스템을 개발하고자 한다.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.11-16
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• 2020

In this paper, system that includes multiple unmanned aerial vehicles (UAVs) are considered. The vehicles are equipped with a mission computer for a specific mission and equipment. The mission equipment operates based on the time of mission computer. Also, data collected by flight computer and mission computer is saved with the time of each operating system. Generally, time offset between multiple computers always exists, though the computers are connected to the Internet. When the data collected by multiple computers is combined, the time offset causes damage on reliability of the combined data. Computers that connected to the Internet are synchronized by network time protocol (NTP). This paper proposes a system that the time of multiple mission computers are synchronized by the same NTP server to minimize the time offset. In the results of the measurement, the system time offset of multiple mission computer is maintained within 10ms from the system time of the server computer.