• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.1021-1031
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• 2020

With the advent of industry 4.0 technologies like the artificial intelligence and the autonomous flight, 'Urban Air Mobility (UAM)' is being considered as an effective alternative to resolve the ground urban traffic congestion. Accordingly, many companies in the world including Korea are investigating on the development of UAM vehicles and operation systems. In this study, after identifying and classifying the essential elements of the UAM operation, the UAM system operational concept has been derived, then detailed analyses for each element has been performed. Based on the conceptual analysis of the UAM operation system, UAM flight routes in Seoul and Gyeong-In area have been established and confirmed to be operable through the performance analysis of UAM vehicles. The flight route analysis in this study is expected to be applied to UAM flight routes establishment in various cities in the future.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.262-269
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• 2016

Flight of an autonomous unmanned aerial vehicle (UAV) generally consists of four steps; take-off, ascent, descent, and finally landing. Among them, autonomous landing is a challenging task due to high risks and reliability problem. In case the landing site where the UAV is supposed to land is moving or oscillating, the situation becomes more unpredictable and it is far more difficult than landing on a stationary site. For these reasons, the accurate and precise control is required for an autonomous landing system of a UAV on top of a moving vehicle which is rolling or oscillating while moving. In this paper, a vision-only based landing algorithm using dynamic gimbal control is proposed. The conventional camera systems which are applied to the previous studies are fixed as downward facing or forward facing. The main disadvantage of these system is a narrow field of view (FOV). By controlling the gimbal to track the target dynamically, this problem can be ameliorated. Furthermore, the system helps the UAV follow the target faster than using only a fixed camera. With the artificial tag on a landing pad, the relative position and orientation of the UAV are acquired, and those estimated poses are used for gimbal control and UAV control for safe and stable landing on a moving vehicle. The outdoor experimental results show that this vision-based algorithm performs fairly well and can be applied to real situations.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.956-961
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• 2007

We propose a new distance measurement method and local positioning system for the autonomous mobile robots localization. The distance measurement method is able to measure long-range distances with a high accuracy by using ultrasonic sensors. The time of flight of the ultrasonic waves include various noises is calculated accurately by the proposed period detecting method. The proposed local positioning system is composed of four ultrasonic transmitters and one ultrasonic receiver. The ultrasonic transmitter and receiver are separated but they are synchronized by RF (Radio frequency) signal. The proposed system using ultrasonic waves is represented as USAT(Ultrasonic Satellite System). USAT is able to estimate the position using the least square estimation. The experimental results show that the proposed local positioning system enables to estimate the absolute position precisely.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.316-322
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• 2023

The increasing popularity of autonomous unmanned aerial vehicles (UAVs) can be attributed to their wide range of applications. 3D path planning is one of the crucial components enabling autonomous flight. In this paper, we present a novel 3D path planning algorithm that generates and utilizes curvature-based trajectories. Our approach leverages circular properties, offering notable advantages. First, circular trajectories make collision detection easier. Second, the planning procedure is streamlined by eliminating the need for the spline process to generate dynamically feasible trajectories. To validate our proposed algorithm, we conducted simulations in Gazebo Simulator. Within the simulation, we placed various obstacles such as pillars, nets, trees, and walls. The results demonstrate the efficacy and potential of our proposed algorithm in facilitating efficient and reliable 3D path planning for UAVs.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.255-261
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• 2020

We consider the problem of autonomously flying a quadcopter in indoor environments. Navigation in indoor settings poses two major issues. First, real time recognition of the marker captured by the camera. Second, The combination of the distributed images is used to determine the position and orientation of the quadcopter in an indoor environment. We autonomously fly a miniature RC quadcopter in small known environments using an on-board camera as the only sensor. We use an algorithm that combines data-driven image classification with image-combine techniques on the images captured by the camera to achieve real 3D localization and navigation.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.101-107
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• 2007

A coaxial rotor flying robot is developed for surveying and reconnoitering various circumstances under calamity environment. The robot has two contrarotating rotors on a common axis, an embedded microcontroller, an IMU(Inertial Measurement Unit), an IR sensor for height control, a micro camera for surveillance, ultrasonic position sensors and wireless communication devices. A bell-bar mounted on the top of the upper rotor hub increases stability and improves flight performance. In this paper, we present a dynamic model of a coaxial rotor flying robot and design an embedded controller far the robot, and implement them to control the developed flying robot. Experimental results show that the proposed controller is valid for autonomous hovering and position control.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.490-498
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• 2010

This paper presents an autonomous target tracking approach and technique for transmitting ground control station image periodically for an unmanned aerial vehicle using onboard gimbaled(pan-tilt) camera system. The miniature rotary UAV which was used in this study has a small, high-performance camera, improved target acquisition technique, and autonomous target tracking algorithm. Also in order to stabilize real-time image sequences, image stabilization algorithm was adopted. Finally the target tracking performance was verified through a real flight test.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.95-99
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• 1998

We introduce an autonomous flying system using a model-helicopter. A feature of the helicopter is that autonomous flight is realized on the low-cost compact model-helicopter. Our helicopter system is divided into two parts. One is on the helicopter, and the other is on the land. The helicopter is loaded with a vision sensor and an electronic compass including a tilt sensor. The control system on the land monitors the helicopter movement and controls. We firstly introduce the configuration of our helicopter system with a vision sensor and an electronic compass. To determine the 3-D position and posture of helicopter, a technique of image recognition using a monocular image is described based on the idea of the sensor fusion of vision and electronic compass. Finally, we show an experiment result, which we obtained in the hovering. The result shows the effectiveness of our system in the compact model-helicopter.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1928-1929
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• 2011

무인항공기란(Unmanned Aerial Vehicle : UAV)란 일반적으로 조종사 없이 사전에 입력된 프로그램에 따라 또는 비행체 스스로 주위환경(장애물, 항로)을 인식하고 판단하여 자율 비행(Autonomous Flying)하는 비행체를 말한다. 본 논문에서는 항법센서(Attitude Heading Referance System: AHRS)를 비행제어 시스템과 통합한 시스템에 관하여 다루었다.