• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.1088-1098
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• 2020

This paper proposes an obstacle avoidance method using a depth polar grid. Depth information is a crucial factor for determining the safe path for collision-free navigation of unmanned aerial vehicles (UAVs) as it can perceive the distance to the obstacles effectively. However, the existing depth-camera-based approaches for obstacle avoidance require computational y expensive path planning algorithms. We propose a simple navigation method using the polar-grid of the depth information obtained from the camera with narrow field-of-view(FOV). The effectiveness of the approach was validated by a series of experiments using software-in-the-loop simulation in a realistic outdoor environment. The experimental results show that the proposed approach successfully avoids obstacles using a single depth camera with limited FOV.

• 대한임베디드공학회논문지
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• 제15권1호
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• pp.25-33
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• 2020

Multipath routing protocols with unmanned aerial vehicles have been proposed to improve reliability in tactical ad hoc networks. Most of existing studies tend to establish the paths with multiple metrics. However, these approaches suffer from link loss and congestion problems according to the network condition because they apply same metric for both ground and air path or employ the simple weight value to combine multiple metrics. To overcome this limitation, in this study, we propose new routing metrics for path over unmanned aerial vehicles and use the multi-criteria decision making (MCDM) method to determine the weight factors between multiple metrics. For the case studies, we extend the ad-hoc on-demand distance vector protocol and propose a strategy for modifying the route discovery and route recovery procedure. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in tactical ad hoc networks.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• 한국항공우주학회지
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• 제39권12호
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• pp.1124-1132
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• 2011

본 논문에서는 2차원 공간에서 기동하는 고정익 무인항공기의 장애물 회피를 위한 부드러운 경로궤적을 생성하는 문제를 다룬다. 2차원 장애물맵의 이산화 모델링을 위해 육각형 격자를 채택하였고, 이는 사각형 격자에 비해 연결성이 높아 부드러운 경로궤적 생성이 가능하도록 하였다. 특히 본 논문에서 제안된 경로템플릿 기법은 일정거리 단위로 조합 가능한 대표경로들(경로템플릿)을 사용하여 무인항공기의 기준경로를 생성하는 방법이고, 온라인 경로궤적 생성에서 계산량을 줄여 메모리 및 연산리소스가 제한되는 소형 오토파일럿에서도 적용이 가능하다는 장점이 있다.

• 로봇학회논문지
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• 제16권2호
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• 항공우주시스템공학회지
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• 제18권3호
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• pp.1-7
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• 2024

UAV (Unmanned Aerial Vehicle)는 물류, 산업, 운송 등 다양한 산업에서 그 활용처가 확대되고 있다. 하지만 다수의 UAV를 운용하기 위해서는 안전하고 효율적인 UAV 자가구성 통신망을 계획하는 것이 우선적으로 이루어져야 한다. 본 연구에서는 보로노이 다이어그램을 활용하여 안전하고 효율적인 UAV 자가구성 통신망을 계획하는 방법을 다음 3가지 단계로 제시한다: 1)장애물들을 이용한 보로노이 다이어그램 생성, 2)경로를 생성하기 위해 고려해야 할 장애물 선별, 3)최적 경로 계획 및 경로 출력. 본 연구에서 제시한 방법은 실제 운용 시 UAV들의 최적 통신경로를 계획하는 것이 실시간으로 가능한 것을 실험을 통해 검증하였다.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.883-890
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• 2021

In this study, joint analysis was conducted on the rock slope by aerial surveying using UAV. Aerial photos were taken using UAV to measure the directionality of the rock slope exposed to the site, and the directionality of the joint was analyzed using the photographed photos. UAV photography was taken under conditions of 90% overlap and an altitude of 50m. The photographing path was measured in the horizontal, vertical, and oblique directions based on the slope, and the joint characteristics were analyzed. Aerial surveying research on the joint directionality analysis of rock slopes is still incomplete, and the method for accurate joint directionality analysis is not presented strategically, so it is difficult to apply it in design. Through the results of this study, we would like to propose an flight photographing technique for the investigation of rock joints. As a result of the study, in the case of the joint investigation of the rock slope using UAV, it was necessary to change conditions such as altitude, aerial photography route, and overlap according to the size of the joint according to the site conditions.

• 로봇학회논문지
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• 제18권3호
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• pp.316-322
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• 2023

The increasing popularity of autonomous unmanned aerial vehicles (UAVs) can be attributed to their wide range of applications. 3D path planning is one of the crucial components enabling autonomous flight. In this paper, we present a novel 3D path planning algorithm that generates and utilizes curvature-based trajectories. Our approach leverages circular properties, offering notable advantages. First, circular trajectories make collision detection easier. Second, the planning procedure is streamlined by eliminating the need for the spline process to generate dynamically feasible trajectories. To validate our proposed algorithm, we conducted simulations in Gazebo Simulator. Within the simulation, we placed various obstacles such as pillars, nets, trees, and walls. The results demonstrate the efficacy and potential of our proposed algorithm in facilitating efficient and reliable 3D path planning for UAVs.

• 로봇학회논문지
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• 제16권3호
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• pp.216-222
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• 2021

Recently, various robots are being used for the purpose of structural inspection or safety diagnosis, and their needs are also rising rapidly. Among the structural inspection using robots, a lot of researches has recently been conducted on inspection of various facilities and structures using an unmanned aerial vehicle (UAV). However, since GNSS (Global Navigation Satellite System) signals cannot be received in an environment near or below structures, the operation of UAVs has been done manually. For a stable autonomous flight without GNSS signals, additional technologies are required. This paper proposes the autonomous flight system for structural inspection consisting of simultaneous localization and mapping (SLAM), path planning, and controls. The experiments were conducted on an actual large bridge to verify the feasibility of the system, and especially the performance of the proposed SLAM algorithm was compared through comparative analysis with the state-of-the-art algorithms.

• International Journal of Aeronautical and Space Sciences
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• 제8권1호
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• pp.54-65
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• 2007

Parameter optimization technique is applied to planning UAVs(Unmanned Aerial Vehicles) path under artificial enemy radar threats. The ground enemy radar threats are characterized in terms of RCS(Radar Cross Section) parameter which is a measure of exposure to the radar threats. Mathematical model of the RCS parameter is constructed by a simple mathematical function in the three-dimensional space. The RCS model is directly linked to the UAVs attitude angles in generating a desired trajectory by reducing the RCS parameter. The RCS parameter is explicitly included in a performance index for optimization. The resultant UAVs trajectory satisfies geometrical boundary conditions while minimizing a weighted combination of the flight time and the measure of ground radar threat expressed in RCS.