• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.740-756
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• 2017

This paper proposes a feedback-linearization-based control algorithm for multirotor unmanned aerial vehicles (UAVs). The feedback linearization scheme is highly efficient for considering nonlinearity between the rotational and translational motion of multirotor UAVs. We also propose a dynamic equation that reflects the aerodynamic effects of the vehicles; the equation's parameters can be determined through curve fitting using actual flight data. We derive the feedback linearization controller from the proposed dynamic equation, and propose a Luenberger observer to attenuate measurement noises. The proposed algorithm is implemented using our in-house flight control computer, and we describe its implementation in detail. To investigate the performance of the proposed algorithm, we carry out two flight scenarios: the first scenario, an autonomous landing on a moving platform, is a test of maneuverability; the second, picking up and replacing an object, test the algorithm's accuracy. In these scenarios, the proposed algorithm precisely controls multirotor UAVs, and we confirm that it can be successfully applied to real flight environments.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.3
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• pp.274-282
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• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

• Smart Structures and Systems
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• v.33 no.2
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• pp.105-118
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• 2024

In order to realize tiny bridge crack discovery by UAV-based machine vision, a novel method combining deep learning and tensor voting is proposed. Firstly, the grid images of crack are detected and descripted based on SE-ResNet50 to generate feature points. Then, the probability significance map of crack image is calculated by tensor voting with feature points, which can define the direction and region of crack. Further, the crack detection anchor box is formed by non-maximum suppression from the probability significance map, which can improve the robustness of tiny crack detection. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method in the Xiangjiang-River bridge inspection. Compared with the original tensor voting algorithm, the proposed method has higher accuracy in the situation of only 1-2 pixels width crack and the existence of edge blur, crack discontinuity, which is suitable for UAV-based bridge crack discovery.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.857-866
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• 2022

Fixed-wing UAVs have long endurance and range capabilities compared to other aerial platforms. These advantages led fixed-wing UAVs to become a popular platform for reconnaissance missions in the military. In this research, we modeled fixed-wing UAVs, including the landing gear model and developed a guidance and control system for flight control computers to construct a HILS environment. We also developed an autopilot system that includes automated take-off, cruise, and landing control for UAVs. We also retrived the Aerodynamic coefficients an UAV using Datcom and AVL software and used them for 6 degrees of freedom modeling. The Flight control computer calculates guidance commands using the Carrot chasing guidance law after distinguishing the condition of the UAV based on 16 pre-defined flight modes and calculates control inputs using Nonlinear Dynamic Inversion (NDI) control scheme. We used RTNngine to integrate the Simulink model and flight control computer for HILS environment formulation.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.529-536
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• 2017

The general ground control system has control and information display functions for the operation of a single unmanned aerial vehicle. Recently, the function of the single ground control system extends to the operation of multiple UAVs. As a result, operators have been exposed to more diverse tasks and are subject to task overload due to various factors during their mission. This study proposes an adaptive ground control system that reflects the operator's condition through the task overload measurement of multiple UAV operators. For this, the ground control software is developed to control multiple UAVs at the same time, and the simulator with six degree-of-freedom aircraft dynamics is constructed for realistic human-machine-interface experiments by the operators.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.69-75
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• 2019

Remotely Piloted Aircraft (RPA) controls as a type of unmanned aerial vehicle (drone) is growing rapidly and its flight controller stick disposition is required standardization. We should standardize RPA drone flight control disposition because the flight pilot of RPA is hard to be trained so the flight controller stick differences impairs safety and wastes time and effort of flight controller industry. So this study researches the on-going standardization of RPA drone flight control disposition in Korea and foreign countries. Also this paper analyzes and researches of expert about RPA drone flight controller function and application of flight control mode. I accomplished expert research about standardization plan of unmanned flight control mode and confirm the necessity. Nowadays mode1 and 2 are mostly used in Korea so I carried out preference investigation for two modes. There were 4 preferences choices of RPA drone control mode necessity (importance) and recommendation of standardization modes. They answered that necessity of standardization is important considering pilot training, flight safety and positive development of drone industry. The result of standardization mode preference is that they prefer mode 2 (drone maker 86%, training facilities and research facilities 58%, government bureau 60%). Overall preference result shows that mode 1 24%, mode 1&2 16%, mode 2 60%. So they preferred mode 2 by 60%. The differences between two modes are the direction of throttle and pitch. Direction of throttle and pitch operate opposite way. They prefer mode 2 because mode 2 has similarities of manned flight control mode. Significance of this study is that it showed the necessity of standardization and flight control preference in a quantitative way. It will help drone standardization in related industries and development direction near future.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1089-1100
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• 2018

In this paper, we analyze the feasibility of establishing a precise sensor model for high-resolution satellite imagery using unified control points. For this purpose, we integrated unified control points and the aerial orthoimages from the national land information map (http://map.ngii.go.kr/ms/map/NlipMap.do) operated by the National Geographic Information Institute (NGII). Then, we collected the image coordinates corresponding to the unified control point's location in the satellite image. The unified control points were used as observation data for establishing a precise sensor model. For the experiment, we compared the results of precise sensor modeling using GNSS survey data and those using unified control points. Our experimental results showed that it is possible to establish a precise sensor model with around 2 m accuracy when using unified control points.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.473-483
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• 2015

This paper reports the single-input-single-output cascade control by using 1-axis attitude control test-bench for quad-rotor UAV. The test-bench was designed as a see-saw shape using 2 motors and propellers, and to enable changing the center of gravity with the center of gyration using ballast. The experiment was carried out by constructing a PID-PID controller having a cascade structure with the test-bench. The SIMC based PID gain tuning process, which makes PID gain tuning easy, was grafted to cascade control. To graft SIMC method, the system parameter estimation result was conducted with second order time delay model by using Matlab-Simulink. Gain tuning was conducted by simulating with estimated system parameter. In this paper, the conventional application of SIMC was conducted and improved application was proposed for improving stability at tuning process.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.25-31
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• 2008

As we choose ground control points for aerial triangulation, we have a lot of problems in a mountain, a costal area, a desert, the foreshore etc because they don't have clear topography for control points and it spends a lot of cost and occurs problems of accuracy. In this study, we compare and analyze between ground control points from LiDAR intensity, digital map with ground control points from the field survey as doing AT each. As the result, the average error was ${\pm}1.02m$ from using LiDAR intensity, ${\pm}1.13m$ from using digital map. this result can present the control points from LiDAR intensity is 0.11m better than from digital map.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.83-90
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• 2020

Disasters are causing significant damage to the lives and property of our society and are recognized as social problems that need to be solved nationally and globally. The 4th industrial revolution technologies affecting society as a whole such as the Internet of Things(IoT), Artificial Intelligence(AI), Drones(Unmanned Aerial Vehicles), and Big Data are continuously absorbed into the disaster and safety industries as scientific and technological tools for solving social problems. Very soon, twenty-nine domestic UAV-related organizations/companies will complete the construction of a multicopter type small UAV integrated system ('17~'20) that can be operated at disaster and security sites. The current work considers and proposes the mid-to-long term R&D direction of disaster UAV as a strategic asset of the national disaster response system. First, the trends of disaster and safety industry and policy are analyzed. Subsequently, the development status and future plans of small UAV, securing shortage technology, and strengthening competitiveness are analyzed. Finally, step-by-step R&D direction of disaster UAV in terms of development strategy, specialized mission, platform, communication, and control and operation is proposed.