• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.195-202
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• 2017

Ortho images created by aerial photogrammetry have been used in large areas but they are uneconomical for small areas and continuous change observation. The drones have been developed for military purposes, and recently they are being used crop management and analysis, broadcast relay, meteorological observation and disaster investigation and so on. Also there were a lot of studies of expensive commercial drone. In this paper, lower price self-assembly drone usable for in small areas, Obtained images and produced Orthomosaic and DSM using mission planner which is a normal digital camera and open source program, and postprocessing was used Pix4d software. GCP errors are X-coordinate 3.4cm, Y-coordinate 2.4cm, Z-coordinate 4.2cm. It seems like the self-assembly drone can be used for various fields.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.48-54
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• 2020

Researchers recognized air pollution changes causing diseases and difficulties in living due to environmental pollution following various human activities, and have studied how to avoid fine dust harmful to the human respiratory system to be healthy. To this end, Arduino is used to equip fine dust level sensors in drones to measure the fine dust levels, visualize the measurements with LED indicator colors depending on the measurements to inform users of the danger of fine dust, and use the benefits of drones to specify dangerous fine dust zones and measure the fine dust levels. Users can see the changes depending on the fine dust levels in real time with the LED indicators. This will contributes to measuring fine dust levels easily in dangerous areas. Mission Planner (ArduPilot) is used to set up the GPS of drone, and store the data from the dust sensor as contents. This study aims to establish a method for improving the environment to measure fine dust levels with drones with LED indicators for fine dust, and reduce fine dust.

• ETRI Journal
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• v.43 no.4
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• pp.580-593
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• 2021

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.5
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• pp.317-324
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• 2015

In his paper, we propose the graphic-based direction tracking system that be able to detect the current location and direction of the flight object and virtually run the pointing to the flight direction when a small UAV is located in the occlusion area behind buildings or obstacles in the moving surveillance systems. Based on the experimental results about the simulation flight path extracted from the Mission Planner we found the proposed system operates the desired flight mission effectively in tracking.

• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.223-228
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• 2008

In order to acquire the images requested by users, it is very important to calculate mission schedule parameters such as imaging execution time and attitude tilt angle accurately. These parameters are based on orbit prediction. This paper describes the accuracy of orbit propagation for image planning. The orbit prediction data from PSS and MAPS has a certain discrepancy due to different orbit propagator. It is necessary for mission planner to confirm this value during mission planning phase. The pointing error which means the difference between target center and real image received is calculated and analyzed using KOMPSAT-2 image data.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.424-434
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• 2012

This paper presents a path planning algorithm of the unmanned aerial vehicle for the neutralization of the enemy firepower. The long range firepower of the ememy is usually located at the rear side of the mountain which is difficult to bomb. The path planner not only consider the differential constraints of the Unmanned Aerial Vehicle (UAV) but also consider the final approaching angle constraint. This problem is easily solved by incorporating the analytical upper bounded continuous curvature path smoothing algorithm into the Rapidly Exploring Random Tree (RRT) planner. The proposed algorithm can build a feasible path satisfying the kinematic constraints of the UAV on the fly. In addition, the curvatures of the path are continuous over the whole path. Simulation results show that the proposed algorithm can generate a feasible path of the UAV for the bombing mission regardless of the posture of the tunnel.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1272-1277
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• 2014

This article describes a path planning algorithm for fixed-wing UAVs when a real terrain should be considered. Nowadays, many UAVs are required to perform mission flights near given terrain for surveillance, reconnaissance, and infiltration, as well as flight altitude of many UAVs are relatively lower than typical manned aerial vehicles. Therefore, real terrain should be considered in path planning algorithms of fixed-wing UAVs. In this research, we have extended a spline-$RRT^*$ algorithm to three-dimensional planner. The spline-$RRT^*$ algorithm is a $RRT^*$ based algorithm, and it takes spline method to extend the tree structure over the workspace to generate smooth paths without any post-processing. Direction continuity of the resulting path is guaranteed via this spline technique, and it is essential factor for the paths of fixed-wing UAVs. The proposed algorithm confirm collision check during the tree structure extension, so that generated path is both geometrically and dynamically feasible in addition to direction continuity. To decrease degrees of freedom of a random configuration, we designed a function assigning directions to nodes of the graph. As a result, it increases the execution speed of the algorithm efficiently. In order to investigate the performance of the proposed planning algorithm, several simulations are performed under real terrain environment. Simulation results show that this proposed algorithm can be utilized effectively to path planning applications considering real terrain.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.178-186
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• 2006

기상 수치예보는 (Numerical Weather Pridiction, NWP)는 바람, 기온, 등과 같은 기상요소의 시간 변화를 나타내는 물리방정식을 컴퓨터로 풀어 미래의 대기 상태를 예상하는 과학적인 방법으로 지구를 상세한 격자 2진부호(GRIdded Binary, 이하 GRIB)로 나누어 그 격자점에서의 값으로 대기 상태를 나타낸다. 지구 각지에서의 각종 관측자료를 기초로 격자점상의 현재값을 구한다. 대용량의 격자데이터는 이진형태이어서 컴퓨터, 서버 저장장치에서 동일형태 데이터로 존재한다. 우리나라 최초의 저궤도 관측 위성인 다목적 실용위성 KOMPSAT-1호(이하, 아리랑 위성1호)는 전자광학카메라(Electro Optical Camera, EOC)를 탑재하여 1999년 12월 21일에 발사된 이후 2006년 1월 현재까지 6여년간 성공적으로 임무를 수행, 7049여회의 영상을 획득하여 국가적으로 귀중한 자료로 활용하고 있다. 아리랑 위성1호는 일일 2-3회 EOC영상을 획득하고 있으며, 임무계획(Mission Planning)은 MP(Mission Planner)가 사용자로부터 자료를 수집하여 임무분석 및 계획 서브시스템(MAPS)에 의해 계산되어진 위성의 제도예측 데이터에 촬영하고자하는 목표지점 좌표를 입력하여 자동명령생성기(KSCG)에 의해 계산된 촬영 경사각도(Tilt)값을 위성에 전송하여 목표지역의 영상을 획득하게 된다. 위성영상 획득에 있어 고가의 위성을 운영하면서 기상의 상태를 정확히 예측하여 실패없이 유효한 영상을 획득하는 것이 무엇보다 중요하다. 본 논문에서는 효율적인 위성임무계획을 위한 기상수치예보 자료를 분석하여 앞으로 발사하게 될 고해상 카메라 탑제위성인 아리랑 위성2호와 3호에 적용하고자 한다. the sufficient excess reactivity to override this poisoning must be inserted, or its concentration is decreased sufficiently when its temporary shutdown is required. As ratter of fact, these have an important influence not only on reactor safety but also on economic aspect in operation. Considering these points in this study, the shutdown process was cptimized using the Pontryagin's maximum principle so that the shutdown mirth[d was improved as to restart the reactor to its fulpower at any time, but the xenon concentration did not excess the constrained allowable value during and after shutdown, at the same time all the control actions were completed within minimum time from beginning of the shutdown.및 12.36%, $101{\sim}200$일의 경우 12.78% 및 12.44%, 201일 이상의 경우 13.17% 및 11.30%로 201일 이상의 유기의 경우에만 대조구와 삭제 구간에 유의적인(p<0.05) 차이를 나타내었다.는 담수(淡水)에서 10%o의 해수(海水)