• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.109-117
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• 2022

This paper proposes a method for detecting flight anomalies of drones through the difference between the command of flight controller (FC) and the navigation solution. If the drones make a flight normally, control errors generated by the difference between the desired control command of FC and the navigation solution should converge to zero. However, there is a risk of sudden change or divergence of control errors when the FC control feedback loop preset for the normal flight encounters interferences such as strong winds or navigation sensor abnormalities. In this paper, we propose the method with a deep neural network model that predicts the control error in the normal flight so that the abnormal flight state can be detected. The performance of proposed method was evaluated using the real-world flight data. The results showed that the method effectively detects anomalies in various situation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.666-671
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• 2019

The flight controller(FC) used in small-sized drone was developed as simple structure does not perform complex operations because it uses different MCU with large-sized drone. Also, the balance control of small-sized drone should be simpler than Kalman filter using complex filter and the method using Complementary filter has relatively more operations. So, the method to realize the balance control on small-sized drone effectively using two-track control operating as proper method for above is suggested in this research. This method is a system maintaining effective balance with simple structure and less operations by operating adaptively for the unbalance of the drone with the acceleration sensor with the advantage which performing accurate correction by data processing for long term change and gyroscope sensor maintaining the balance of the drone by data processing for short term change. It is confirmed that stable operation was performed mostly based on the test result for repeatable test more than 100 times using two-track control and it maintained normal state operation more than 98% excluding the difficulty of maintaining normal operation when meets sudden and rapid wind yet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.583-584
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• 2022

Due to the development of drones, drone missions are performed in various fields, and BVLOS (Beyond Visual Line Of Sight) flight is performed in a wide area. Most drones operate through radio frequency (RF) communication and can only fly in a limited radius of about 1-2 km. To overcome this, in this paper, we propose a multi-communication protocol-based drone control system to control drones performing missions in BVLOS using RF and LTE (Long Term Evolution). The proposed system consists of a control unit and a drone unit. The control unit transmits one control signal generated from the remote controller through RF and LTE. The drone unit classifies the control signal transmitted through RF and LTE according to the priority of the communication protocol and delivers it to the FC (Flight Controller). Through the proposed control system, it is possible to overcome the RF communication distance limit and prevent the communication disconnection situation.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.54-60
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• 2018

In this paper, we propose an efficient automatic control method for the collision avoidance of drones. In general, the drones are controlled by transmitting to the flight control (FC) module the received PWM signals transmitted from a RC controller which transduce movements of the knob into PWM signal. We implemented the collision avoidance module in-between receiver and FC module to monitor and change the throttle, pitch and roll control signals to avoid drone collision. In order to avoid the collision, a LiDAR distance sensor and a servo-motor are installed and periodically measure the obstacle distance within -45 degrees from 45 degrees in flight direction. If the collision is predicted, the received PWM signal is changed and transmitted to the FC module to prevent the collision. We applied our proposed method to a hexacopter and the experimental results show that the safety is improved because it can prevent the collision caused by the inadvertency or inexperienced maneuver.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.867-874
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• 2021

The IoT (Internet of Things) technology is rapidly becoming an important consideration in many engineering fields in the current 4th industrial era. In recent years, the concepts of digital shipbuilding and smart factories have been adopted as trends in shipyards. However, there is active interest in research on implementing autonomous driving in autonomous vehicles and airplanes, which is currently available in commercial form in a limited capacity. The present study is regarding the path-tracking performance of a boat to accomplish an autonomous driving mission using a flight controller (FC) and real-time kinematic (RTK) global positioning system (GPS) based on an open-source Ardupilot; an actual sea test is also performed using this system on a calm lake. The boat's mission is to evaluate the maneuverability of the self-driving process to a specific point and returning to the home position. For a given speed, the difference between the preset mission trajectory and actual operational trajectory was analyzed, and a series of studies were conducted on the applicability of the system to ships. In addition, the movements and maneuverability of the OmniX-type hull with four propellers were investigated, and the driving path-tracking performance was observed to increase by a maximum of 48%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.141-142
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• 2018

현재 시중에 판매되는 비행체들은 수동으로 조종을 하고 조종법이 미숙한 사람들은 다루기 힘들며 레저용으로 짧은 비행거리를 가지고 있고 간단한 영상촬영, 지형측정 등의 간단한 용도를 가졌다. 본 연구에서는 무인기의 FC(Flight Controller)의 인터페이스를 이용한 원리, 동작을 통하여 사용자의 조종 능력 향상을 기대할 수 있으며 Arduino 와 Pixhawk를 이용한 수직 이착륙기를 제작하여 활주로에 대한 제약을 없애고 멀티콥터와 비교하여 보다 좀 더 효율적인 비행을 할 수 있고자 한다.