• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.45 no.8
• /
• pp.647-661
• /
• 2017

This paper presents a robust method for autonomously landing on small bodies. Autonomous landing is accomplished by generating and following reference position and attitude profiles. The position and attitude tracking controllers are based on discrete sliding mode control, which explicitly treats the discrete and impulsive natures of thruster operation. Vision-based inertial navigation is used for autonomous navigation for landing. Numerical simulation is carried out to evaluate the performance of the proposed method in a realistic situation with environmental uncertainties.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.15-18
• /
• 2023

UAV는 군사용을 처음 시작으로 근래에 취미용 드론의 급격한 성장과 더불어 최근 기후변화, 교통혼잡, 범죄 예방 등 여러 사회 문제 해결을 위한 드론의 필요성이 증가함에 따라 건설, 교통, 농업, 에너지, 엔터테인먼트 등 다양한 산업과 여러 사회 서비스로 그 필요성이 확대되고 있다. 본 연구는 이러한 사회적 흐름에 따라 인공지능 기술을 통한 드론의 활용성을 확대하고 GPS 수신이 안 되는 환경에서 딥러닝 객체 탐지 모델을 활용한 자율 착륙을 연구를 목표로 한다. GPS 신호는 실내와 같은 환경 혹은 지하, 교량 아래, 산속 등과 같은 곳에서는 수신이 어렵다. 이를 극복하고자 GPS 신호수신이 어려운 지역에서 GPS 수신기를 통해 받는 위치 정보 대신 드론에 장착된 카메라를 통해 전달받는 영상에서 착륙할 지점을 인식하고 카메라를 통해 받는 영상 정보만 이용하여 목표지점으로 하강하는 방식으로 자율 착륙을 유도한다. 딥러닝 중 경량화 모델을 활용하여 소형 드론에서 실시간으로 착륙 지점을 감지하기 위해 최적화 과정을 진행해 실시간 자율 착륙이 가능하게 하였다. 본 연구를 통해 드론의 착륙에 있어 GPS 수신기와 사람의 조종에 대한 의존도를 낮출 수 있을 것으로 기대한다.

• Journal of Industrial Convergence
• /
• v.18 no.1
• /
• pp.79-85
• /
• 2020

Recently, the RPAS(Remote Piloted Aircraft System), by remote control and autonomous navigation, has been increasing in interest and utilization in various industries and public organizations along with delivery drones, fire drones, ambulances, agricultural drones, and others. The problems of the stability of unmanned drones, which can be self-controlled, are also the biggest challenge to be solved along the development of the drone industry. drones should be able to fly in the specified path the autonomous flight control system sets, and perform automatically an accurate landing at the destination. This study proposes a technique to check arrival by landing point images and control landing at the correct point, compensating for errors in location data of the drone sensors and GPS. Receiving from the Google Map API and learning from the destination video, taking images of the landing point with a drone equipped with a NAVIO2 and Raspberry Pi, camera, sending them to the server, adjusting the location of the drone in line with threshold, Drones can automatically land at the landing point.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.269-270
• /
• 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 the Korean Society for Aeronautical & Space Sciences
• /
• v.45 no.9
• /
• pp.734-745
• /
• 2017

The navigation system of lunar lander are composed of various navigation sensors which have a complementary characteristics such as inertial measurement unit, star tracker, altimeter, velocimeter, and camera for terrain relative navigation to achieve the precision and autonomous navigation capability. The required performance of sensors has to be determined according to the landing scenario and mission requirement. In this paper, the specifications of navigation sensors are investigated through covariance analysis. The reference error model with 77 state vector and measurement model are derived for covariance analysis. The mission requirement is categorized as precision exploration with 90m($3{\sigma}$ ) landing accuracy and area exploration with 6km($3{\sigma}$ ), and the landing scenario is divided into PDI(Powered descent initiation) and DOI(Deorbit initiation) scenario according to the beginning of autonomous navigation. The required specifications of the navigation sensors are derived by analyzing the performance according to the sensor combination and landing scenario.

• Journal of the Korea Society for Simulation
• /
• v.28 no.1
• /
• pp.93-98
• /
• 2019

In case of unmanned aerial vehicles used in modern society, there has been a problem where a human operator should be still needed to control the UAV because of a lower level of autonomy. In this paper, genetic algorithm is selected as a methodology for the autonomy accomplishment and then we verify a possibility of UAV autonomy by applying the GA. The landing is one of the important classical tasks on aerial vehicle and the lunar Landing is one of the most historical events. Autonomy possibility of computer-simulated UAV is verified by landing autonomy method of a falling body equipped with a propulsion system similar to the lunar Lander. When applying the GA, the genom is encoded only with 4 actions (left-turn, right-turn, thrust, and free-fall) and applied onto the falling body, Then we applied the major operations of GA and achieved a success experiment. A major contribution is to construct a simulated UAV where an autonomy of UAV can be accomplished while minimizing the sensor dependency. Also we implemented a test-bed where the possibility of autonomy accomplishment by applying the GA can be verified.

• Journal of Aerospace System Engineering
• /
• v.18 no.2
• /
• pp.47-55
• /
• 2024

The paper presents a docking-type automatic landing system that works in tandem with Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs). The system utilizes a pyramid-shaped landing gear and pad for effective landing. In marine environments, a docking device guides the drone to land securely. To test the system, a ship's behavior was simulated using a 3-DoF motion platform, and the successful operation and utility of the docking-type automatic landing system were demonstrated.

• Journal of Platform Technology
• /
• v.11 no.3
• /
• pp.24-31
• /
• 2023

Recently, interest in UAM (Urban Air Mobility, UAM), which can take off and land vertically in the operation of urban air transportation systems, has been increasing. Therefore, various start-up companies are developing related technologies as eco-friendly future transportation with advanced technology. However, studies on ways to increase safety in the operation of UAM are still insignificant. In particular, efforts are more urgent to improve the safety of risks generated in the process of attempting to land in the city center by UAM equipped with autonomous driving. Accordingly, this study proposes a plan to safely land by avoiding dangerous region that interfere when autonomous UAM attempts to land in the city center. To this end, first, the latitude and longitude coordinate values of dangerous objects observed by the sense of the UAM are calculated. Based on this, we proposed to convert the coordinates of the distorted planar image from the 3D image to latitude and longitude and then use the calculated latitude and longitude to compare the pre-learned feature descriptor with the HOG (Histogram of Oriented Gradients, HOG) feature descriptor to extract the dangerous Region. Although the dangerous region could not be completely extracted, generally satisfactory results were obtained. Accordingly, the proposed research method reduces the enormous cost of selecting a take-off and landing site for UAM equipped with autonomous driving technology and contribute to basic measures to reduce risk increase safety when attempting to land in complex environments such as urban areas.

• Journal of the Korea Convergence Society
• /
• v.8 no.6
• /
• pp.9-16
• /
• 2017

Researchers are now faced with a limited flight time of the hoverable UAV due to the sluggish technological advances of the Li-Po energy density and try to find a bypassing solution for the fully autonomous hoverable UAV mission planning. Although there are several candidate solutions, automated wireless charging is the most likely and realistic candidate and we are focusing on the autolanding strategy of the hoverable UAV in this paper since it is the main technology of it. We developed a hoverable UAV flight simulator including Li-Po battery pack simulator using MATLAB/Simulink and UAV flight and battery states are analyzed. The maximum motor power measured as 1,647 W occurs during the takeoff and cell voltage decreases down to 3.39 V during the procedure. It proves that the two Li-Po battery packs having 22 Ah and connected in series forming 12S1P are appropriate for the autolanding mission planning.

• Journal of Auto-vehicle Safety Association
• /
• v.16 no.2
• /
• pp.20-26
• /
• 2024

The delivery using drones has been attracting attention because it can innovatively reduce the delivery time from the time of order to completion of delivery compared to the current delivery system, and there have been pilot projects conducted for safe drone delivery. However, the current drone delivery system has the disadvantage of limiting the operational efficiency offered by fully autonomous delivery drones in that drones mainly deliver goods to pre-set landing sites or delivery bases, and the final delivery is still made by humans. In this paper, to overcome these limitations, we propose obstacle detection and landing site selection algorithm based on a vision sensor that enables safe drone landing at the delivery location of the product orderer, and experimentally prove the possibility of station-to-door delivery. The proposed algorithm forms a 3D map of point cloud based on simultaneous localization and mapping (SLAM) technology and presents a grid segmentation technique, allowing drones to stably find a landing site even in places without prior information. We aims to verify the performance of the proposed algorithm through streaming data received from the drone.