• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

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

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.829-839
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• 2021

Autonomous system for UAVs has a capability to decide an appropriate current action to achieve the goal based on the ultimate mission goal, context of mission, and the current state of the UAV. We propose a decision-making system that has an ability to operate ISR mission autonomously under the realistic limitation such as low altitude operation with high risk of terrain collision, a set of way points without change of visit sequence not allowed, and position uncertainties of the objects for the mission. The proposed decision-making system is loaded to a Hardware-In-the-loop Simulation environment, then tested and verified using three representative scenarios with a realistic mission environment. The flight trajectories of the UAV and selected actions via the proposed decision-making system are presented as the simulation results with discussion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.187-192
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• 2021

This study proposes a system for take-off in a forest or similar complex environment using an object detector. In the simulator, a raspberry pi is mounted on a quadcopter with a length of 550mm between motors on a diagonal line, and the experiment is conducted based on edge computing. As for the images to be used for learning, about 150 images of 640⁎480 size were obtained by selecting three points inside Kunsan University, and then converting them to black and white, and pre-processing the binarization by placing a boundary value of 127. After that, we trained the SSD_Inception model. In the simulation, as a result of the experiment of taking off the drone through the model trained with the verification image as an input, a trajectory similar to the takeoff was drawn using the label.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1247-1255
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• 2016

The safety and autonomous flight function of micro UAV or drones is crucial to its commercial application. The requirement of own building stable drones is still a non-trivial obstacle for researchers that want to focus on the intelligence function, such vision and navigation algorithm. The paper present a GCS using commercial drone and hardware platforms, and open source software. The system follows modular architecture and now composed of the communication, UI, image processing. Especially, lane-keeping algorithm. are designed and verified through testing at a sports stadium. The designed lane-keeping algorithm estimates drone position and heading in the lane using Hough transform for line detection, RANSAC-vanishing point algorithm for selecting the desired lines, and tracking algorithm for stability of lines. The flight of drone is controlled by 'forward', 'stop', 'clock-rotate', and 'counter-clock rotate' commands. The present implemented system can fly straight and mild curve lane at 2-3 m/s.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.172-175
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• 2016

Time of Flight(ToF) LiDAR(Light Detection And Ranging) technology has been used for distance measurement and object detection by measuring ToF time information. This technology has been evolved into higher precision measurement field such like autonomous driving car and terrain analysis since the retrieval of exact ToF time information is of prime importance. In this paper, as a accuracy indicator of the ToF time information, timing jitter was measured and analyzed through Single-Shot LiDAR system(SSLs) mainly consisting of 1.5um wavelength MOPA LASER, InGaAs Avalanche Photodiode(APD) at 31M free space environment. Additionally, we applied spline interpolation and multiple-shot averaging method on measured data through SSLs to improve ToF timing information.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.479-487
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• 2022

This paper presents the control and guidance algorithm of a KAU-SPUAV(Korea Aerospace University - Solar Powered Unmanned Aerial Vehicle) which is designed and developed in Korea Aerospace University. Aerodynamic coefficients are calculated using the vortex-lattice method and applied to the aircraft's six degrees of freedom equation. In addition, the thrust and torque coefficients of the propeller are calculated using the blade element theory. An altitude controller using thrust was used for longitudinal control of KAU-SPUAV to glide efficiently when it comes across the upwind. Also describes wind estimation technic for considering wind effect during flight. Finally, introduce some guidance laws for endurance, mission and coping with strong headwinds and autonomous landing.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.569-576
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• 2023

An agricultural drones are gradually increasing in utilization due to economic efficiency, and consist of a main frame in charge of flying spray system in charge of moving pesticide to control targets. Therefore, the environment and characteristics of crops should be considered when controlling pesticides using drones and conditions such as systematic flying altitude of flight, speed, and spray time should be changed accordingly. However, pest control work using agricultural drones has different spray effects depending on level the operation proficiency and spray impact. In addition, there are variations in operating standards and control efficiency for agricultural drones, which hinder the distribution of agricultural control drones in the field of pest control work. Therefore, this study attempts to identify the spraying characteristics of agricultural drones, apply the effective spraying time, interval and experimentally verify the system that can calculation of spray area compared to previous studies. Through this experimental verification, it is intended to apply the optimal control process by minimizing the obstacles to pest control work by applying the operation method and systematic figures to agricultural drones.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.2
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• pp.130-137
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• 2012

The underwater glider using conception of Lagrangian method, is a new observation platform to understand the properties of the ocean vertically. In 2011 March, KORDI made a first successful autonomous trip from Hupo to west coast of Uleungdo piloting Littoral Glider of Alaska Native Technology LLC. The journey considered many environmental variables and route vigilantly selected, the glider covered 177 km horizontally and took approximately 6 days (153 hours). Despite the existence of 1 kt eddy current, Sound velocity sampling was conducted from 5 meters and reaching maximum of 200 meters depth at each dive. It successfully collected sound velocity and temperature profile at every 5 seconds totaling up to 1408 profiles using SVT&P sensor. During the flight it was also a mission to check the diverse modes of the glider i.e. spiral, waypoints, heading, drift and hover could function without a defect in a given situation. These modes were thoroughly monitored and it could be considered that the glider handled it well during the flight. As a result of this test flight, it was evident that the given underwater glider could operate under 2kt current environment with users defined heading and depth, also with the payload up to 5 kg without changing internal buoyancy.