• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.2
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• pp.34-43
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• 2022

In Efforts to prevent CFIT accidents so far, have been emphasizing various education measures to minimize the occurrence of human errors, as well as enforcement measures. However, current engineering measures remain in a system (TAWS) that gives warnings before colliding with ground or obstacles, and even actual automatic avoidance maneuvers are not implemented, which has limitations that cannot prevent accidents caused by human error. Currently, various attempts are being made to apply machine learning-based artificial intelligence agent technologies to the aviation safety field. In this paper, we propose a deep reinforcement learning-based artificial intelligence agent that can recognize CFIT situations and control aircraft to avoid them in the simulation environment. It also describes the composition of the learning environment, process, and results, and finally the experimental results using the learned agent. In the future, if the results of this study are expanded to learn the horizontal and vertical terrain radar detection information and camera image information of radar in addition to the terrain database, it is expected that it will become an agent capable of performing more robust CFIT autonomous avoidance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.269-270
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• 2024

최근 드론 산업의 규모가 커지면서 드론을 다양한 분야에 활용하려는 노력이 커지고 있다. 대규모 환경 모니터링, 재난 관리 등에 사용되기 위해서는 장시간 연속 비행이 필요하지만 드론의 배터리 용량 문제로 인해 사람이 직접 배터리를 교체해 주지 않으면 장시간 비행이 어렵다. 본 논문은 드론이 배터리 충전을 위해 자율적으로 착륙해 충전 후 이륙하는 가로등을 활용한 자율 충전 스테이션'을 제안한다. 단순한 무선 충전이 아닌 드론이 자율 비행을 통해 스테이션에 착륙하고 스테이션의 초음파 센서를 통해 착륙이 감지되면 스테이션의 송신부에서 전력을 공급해 드론의 무선 충전이 가능하다. 또한 스테이션의 구조를 원뿔형으로 만들어 드론이 스테이션의 중앙에 정확히 안착되도록 하였다. 자율 드론 충전 스테이션을 통해 배터리 용량 문제를 새로운 방식으로 해결할 수 있고, 업무에 필요한 인력을 최소화함으로서 드론 관제, 환경 모니터링 등 드론을 활용하는 다양한 분야에 도움을 줄 수 있을 것이다.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1181-1188
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• 2014

In this paper, we propose a novel concept foran unmanned delivery service using a cooperative heterogeneous unmanned system consisting of a self-driving car and an unmanned aerial vehicle (UAV). The proposed concept is suitable to deliver parcels in high-density and high-rise urban or residential areas. In order to achieve the proposed concept, we will develop acooperative heterogeneous unmanned system. Customers can order goods using a smartphone application and the order information, including the position of the customer and the order time, and the package is transported automatically by the unmanned systems. The system assigns the tasks suitable for each unmanned vehicle by analyzing it based on map information. Performance is validated by experiments consisting of autonomous driving and flight tests in a real environment. For more evaluation, the landing position error analysis is performed using circular error probability (CEP).

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1028-1036
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• 2004

Ultrasonic sensors are widely used in mobile robot applications to recognize external environments by virtue that they are cheap, easy to use, and robust under varying lighting conditions. In most cases, a single ultrasonic sensor is used to measure the distance to an object based on time-of-flight (TOF) information, whereas multiple sensors are used to recognize the shape of an object, such as a comer, plane, or edge. However, the conventional sequential driving technique involves a long measurement time. This problem can be resolved by pulse coding of ultrasonic signals, which allows multi-sensors to be emitted simultaneously and adjacent objects to be distinguished. Accordingly, this paper presents a new simultaneous coded driving system for an ultrasonic sensor array for object recognition in autonomous mobile robots. The proposed system is designed and implemented. A micro-controller unit is implemented using a DSP, Polaroid 6500 ranging modules are modified for firing the coded signals, and a 5-channel coded signal generating board is made using a FPGA. To verify the proposed method, experiments were conducted in an environment with overlapping signals, and the flight distances fur each sensor were obtained from the received overlapping signals using correlations and conversion to a bipolar PCM-NRZ signal.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.265-270
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• 2005

This paper presents a new attitude stabilization and control of an unmanned helicopter based on neural network compensation. A systematic derivation on the dynamics of an unmanned small-scale helicopter is performed. Combined rotor-fuselage-tail dynamics is derived in body-fixed reference frame with its origin at the C.G. of the helicopter. And the resulting nonlinear equation of motion consists of 6-DOF air vehicle dynamics as well as the rotor flapping and engine torque equations. A simulation model was modified using the existing simulator for an unmanned helicopter dynamic model, which reflects the unmanned test helicopter(CNUHELI). The dynamic response of the refined model was compared with the flight test data. It can be shown that a good coincidence was accomplished between the real unmanned helicopter system and the mathematical model. This dynamic model was linearized for classical controller design using small perturbation method. A Neuro-PD control system was designed for both longitudinal and lateral flight modes, and the results were compared with the PD-only control response. Simulation results show that the proposed Neuro-PD control system demonstrates better performance.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1098-1102
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• 2014

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.765-772
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• 2020

A lot of studies to overcome the limitation of flight time have been studied, since the requirement of complicated mission achievement of aircraft including Unmanned Aerial Vehicles(UAVs) has been increased. The fuel limitation could bring about not enough flight time to accomplish missions. For this reason, the rendezvous maneuver is required to accomplish aerial refueling missions. The rendezvous guidance law based on variable pursuit guidance is designed using Lyapunov stability theory in this study. Numerical simulation is performed to demonstrate the performance of the proposed rendezvous guidance.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.133-145
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• 2011

This paper is about the results in Qualification Management activity performed between the Autonomous Test(AT) season(August. 2008) of Launch Complex and the 2nd flight test season(June. 10, 2010) of KSLV-I. All cryogenic fluids(LOX, $LN_2$) and compressed gases(Air, $GN_2$, GHe) were qualified by qualification management activity during AT(Autonmous Test), QT(Qualification Test) season for LP(Launch Pad) and LVAB(Launch Vehicle Assembly Building) and FT(Flight Test) season of KLSV-I. As the results, total 428 times of check analysis and 111 times of full analysis were performed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.666-673
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• 2013

This paper proposes the performance evaluation test of attitude heading reference system (AHRS) suitable for small high speed autonomous underwater vehicle(AUV). Although IMU can provides the detail attitude information, it is sometime not suitable for small AUV with short operation time in view of price and the electrical power consumption. One of alternative for tactical grade IMU is the AHRS based micro-machined electro mechanical system(MEMS) which can overcome many problems that have inhibited the adoption of inertial system for small AUV such as cost and power consumption. A cost effective and small size AHRS which incorporates measurements from 3-axis MEMS gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for AUV and the attitude calculation algorithm is derived based the coordinate transform equation and Kalman filter. The developed AHRS was validated through various performance tests as like the magnetometer calibration, operating experiments using land mobile vehicle and flight motion simulator (FMS). The test of magnetometer calibration shows the developed MEMS AHRS is robust to the external magent field change and the test with land vehicle proves the leveling error of developed MEMS AHRS is below $0.5^{\circ}/hr$. The results of FMS test shows the fact that AHRS provides the measurement with $0.5^{\circ}/hr$ error during 5 minutes operation time. These results of performance evaluation tests showed that the developed AHRS provides attitude information which error of roll and pitch are below $1^{\circ}$ and the error of yaw is below $5^{\circ}$ and satisfies the required specification. It is expected that developed AHRS can provide the precise attitude measurement under sea trial with real AUV.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.293-300
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• 2009

The rotorcraft-based unmanned aerial vehicle(UAV) capable of performing close-range surveillance and reconnaissance has been developed. Trade studies on mission feasibility led to the adoption of a coaxial rotorcraft with twin rotors counter-rotating in one axis and driven by electric motors. A commercial off-the-shelf flight control computer(FCC) and a radio frequency modem were adopted for autonomous navigation. In order to achieve an aerial view, commercial charge-coupled device camera was also integrated into the vehicle. The performance of the completed vehicle was proved with manual flight test, and mission capability was verified through waypoint navigation flight after being equipped with FCC. This paper treats the whole process of design and system integration for development of the coaxial rotorcraft UAV.