• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.10-20
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• 2024

Recent advancements in autonomous flight technologies for Unmanned Aerial Vehicles (UAVs) have greatly expanded their applicability for various tasks, including delivery, agriculture, and rescue. This article presents a comprehensive survey of path planning techniques in autonomous navigation and exploration that are tailored for UAVs. The robotics literature has studied path and motion planning, from basic obstacle avoidance to sophisticated algorithms capable of dynamic decision-making in challenging environments. In this article, we introduce popular path and motion planning approaches such as grid-based, sampling-based, and optimization-based planners. We further describe the contributions from the state-of-the-art in exploration planning for UAVs, which have been derived from these well-studied planners. Recent research, including the method we are developing, has improved performance in terms of efficiency and scalability for exploration tasks in challenging environments without human intervention. On the basis of these research and development trends, this article discusses future directions in UAV path planning technologies, illustrating the potential for UAVs to perform complex tasks with increased autonomy and efficiency.

• Transactions of the KSME C: Technology and Education
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• v.2 no.2
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• pp.113-124
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• 2014

In developing an aircraft, configuration determination and requirement proofing depend on flight test results. Since the flight tests require much time and high cost, systematic flight test planning and analysis are needed to reduce cost and development time. This paper presents a desirability function approach to present an integrative measure of vibration levels at important positions and suggests a fractional factorial design which is one of the experimental design methods to help perform systematic flight tests. A method to perform flight tests in stages is also suggested to further reduce the number of flight tests.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.563-575
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• 2023

Trajectory planning is a key technology for unmanned aerial vehicles (UAVs) to achieve complex flight missions. In this paper, a terminal constraints conversion-based Gauss pseudospectral trajectory planning optimization method is proposed. Firstly, the UAV trajectory planning mathematical model is established with considering the boundary conditions and dynamic constraints of UAV. Then, a terminal constraint handling strategy is presented to tackle terminal constraints by introducing new penalty parameters so as to improve the performance index. Combined with Gauss-Legendre collocation discretization, the improved Gauss pseudospectral method is given in detail. Finally, simulation tests are carried out on a four-quadrotor UAV model with different terminal constraints to verify the performance of the proposed method. Test studies indicate that the proposed method performances well in handling complex terminal constraints and the improvements are efficient to obtain better performance indexes when compared with the traditional Gauss pseudospectral method.

• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.15-22
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• 2019

In this paper, a global and local flight path system for autonomous flight of the UAV is proposed. The overall system is based on the ROS robot operating system. The UAV in-built computer detects obstacles through 2-D Lidar and generates real-time local path and global path based on VFH and Modified $RRT^*$-Smart, respectively. Additionally, a movement command is issued based on the generated path on the UAV flight controller. The ground station computer receives the obstacle information and generates a 2-D SLAM map, transmits the destination point to the embedded computer, and manages the state of the UAV. The autonomous UAV flight system of the is verified through a simulator and actual flight.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.479-488
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• 2019

The flight test operational procedure artifact includes mission planning, execution methods, and safety measures for each step of test progress. As the development of guided missiles has become more advanced and strategic, flight test has become increasingly complex and broadened. Therefore, increased reliability of the flight test operation procedures was required to ensure test safety. Particularly, the design of the flight test operational procedures required verification through M&S to predict and prepare for the uncertainty in a new test. The relevant studies have published the optimal framework development for flight tests and the model-based improvements of flight test processes, but they lacked the specificity to be applied directly to the flight test operational procedures. In addition, the flight test operational procedures, which consist of document bases, have caused problems such as limitations of analysis capabilities, insensitive expressions, and lack of scalability for the behavior and performance analysis of test resources. To improve these problems, this paper proposes how to design operational procedure of guided missile flight test system by applying MBSE(Model-based Systems Engineering). This research has improved reliability by increasing the ability to analyze the behavior and performance of test resources, and increased efficiency with the scalability applicable to multiple flight tests. That can be also used continuously for the guided missile flight tests that will be developed in the future.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.127-130
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• 2017

In this research, we present a path planning method for an autonomous flight of unmanned aerial vehicles (UAVs) through reinforcement learning under simulated environment. We design the simulator for reinforcement learning of uav. Also we implement interface for compatibility of Deep Q-Network(DQN) and simulator. In this paper, we perform reinforcement learning through the simulator and DQN, and use Q-learning algorithm, which is a kind of reinforcement learning algorithms. Through experimentation, we verify performance of DQN-simulator. Finally, we evaluated the learning results and suggest path planning strategy using reinforcement learning.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.56-63
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• 2016

For air express service providers offering various express delivery services such as overnight delivery and next-business day delivery services, establishing quickly cargo loading plans is one of important issues owing to the characteristics of air express business, i.e., a short amount of time is available to complete all cargo loading operations before flight departure after receiving air express containers, pallets and bulks. On the other hand, one of major concerns in the air cargo loading planning is to make a plan that insures the stability of an aircraft to avoid take-off, flight, and landing accidents. To this end, this paper considers an air cargo loading planning problem, which is the problem of determining locations in the aircraft cargo space where air containers, pallets and bulks to be loaded while insuring the aircraft stability, motivated from DHL and Air Hong Kong. The objective of the problem is to maximize the total revenue gained from loading air express containers, pallets and bulks. To solve the problem, this paper suggests a simulated annealing algorithm to overcome impracticality of the integer programming model developed by a previous study requiring excessive computation time. The results of computational experiments show that the heuristic algorithm is a viable tool for establishing express cargo loading plans as giving robust and good solutions in a short amount of computation time. Scenario analyses are performed to investigate the effect of the current activities of air express carriers on the revenue change and to draw practical implications for air express service providers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.10
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• pp.918-926
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• 2007

Military aircrafts usually operate at the area with lots of threats such as radars and surface-to-air missiles. Aircraft also faces with the unexpected or pop-up threats. Under this environment, a safe flight path should be generated to lead a mission successful. In this paper, a new path planning algorithm is proposed to provide less dangerous flight path efficiently. Of many path planning algorithms, a potential method is considered, because it has advantages of computation efficiency and smooth path generation. Trajectory generation under the condition of maximum range is studied so that the aircraft may reach the target area without refueling. The algorithm to cope with an unexpected situation is also proposed by adopting the concept of initial direction vector, additional force, and a new mapping function. The performance of the proposed algorithms is demonstrated for SEAD (Suppression of Enemy Air Defences) mission by numerical simulation.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2004.11a
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• pp.625-632
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• 2004

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.39-48
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• 2018

The purpose of this study is to verify the stable flight conditions of drones within a limited urban area by using the ICAO(International Civil Aviation Organization) reich model which is using to evaluate civil aircraft stability. The results of the study are summarized as follows. First, in order for the drones flying stably, the horizontal safety separation distance between a drone and another should be at least 1,852M. Second, assuming that no obstacles within 1,852M of horizontal space, two drones can be fly into upper and lower spaces. However there are obstacles such as buildings, it is impossible to secure a 1,852M distance between drones. Third, sensitivity analysis point out that the separation interval($s_x$) of drone aviation has the greatest influence on the TLS(Target Level of Safety). If future research is conducted to lower the numerical values, the safety distance between a drone and another drone will be drastically reduced, allowing more detailed urban space division, and will be presented as a scientific numerical value for establishing a dedicated path for the drones.