• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.9
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• pp.843-852
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• 2009

In this paper, we present design, fabrication, and measured results for a frequency upconverter for a wireless communication system of UAV(Unmanned Aerial Vehicle). The specifications of such wireless communication system requires the special features of maximum range of communication as well as deployment in UAV and repairing. The frequency upconverter operating at $5.25{\sim}5.45\;GHz$ in C-band was designed and fabricated considering such special features. The AGC function was included because the required output power should be constant for optimal system operation. The fabricated upconverter showed a constant output power of $+2{\pm}0.5\;dBm$ for the $-15{\sim}-10\;dBm$ input. Spuriouses were below -60 dBc and the adjacent leakage power was below -40 dBc. In addition, LO sources in the upconverter was implemented using the frequency synthesizer with step 1 MHz. This is for the application to the situation where multiple UAVs employed and the possible change of the permitted frequency band. The synthesizer showed a phase noise of -100 dBc/Hz at the 100 kHz frequency offset.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.419-429
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• 2020

In conducting a mission to explore and track targets using a number of unmanned aerial vehicles(UAVs), performance for that mission may vary significantly depending on the operating conditions of the UAVs such as the number of operations, the altitude, and what future flight paths each aircraft decides based on its current position. However, studies on the number of operations, operating conditions, and flight patterns of unmanned aircraft in these surveillance missions are insufficient. In this study, several types of flight simulations were conducted to detect and determine targets while multiple UAVs were involved in the avoidance of collisions according to various autonomous flight algorithms based by flocking theory, and the results were presented to suggest a more efficient/effective way to control a number of UAVs in target detection missions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• 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.