• 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.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).

• ETRI Journal
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• v.45 no.5
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• pp.735-745
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• 2023

This paper surveys recent multiagent reinforcement learning and neural Myerson auction deep learning efforts to improve mobility control and resource management in autonomous ground and aerial vehicles. The multiagent reinforcement learning communication network (CommNet) was introduced to enable multiple agents to perform actions in a distributed manner to achieve shared goals by training all agents' states and actions in a single neural network. Additionally, the Myerson auction method guarantees trustworthiness among multiple agents to optimize rewards in highly dynamic systems. Our findings suggest that the integration of MARL CommNet and Myerson techniques is very much needed for improved efficiency and trustworthiness.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.765-772
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• 2020

A lot of studies to overcome the limitation of flight time have been studied, since the requirement of complicated mission achievement of aircraft including Unmanned Aerial Vehicles(UAVs) has been increased. The fuel limitation could bring about not enough flight time to accomplish missions. For this reason, the rendezvous maneuver is required to accomplish aerial refueling missions. The rendezvous guidance law based on variable pursuit guidance is designed using Lyapunov stability theory in this study. Numerical simulation is performed to demonstrate the performance of the proposed rendezvous guidance.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.425-430
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• 2024

This paper analyzes the characteristics of various types of unmanned aerial vehicles (drones) for military use and how each type can be utilized in military operations. The scope of the study focuses on the structural features, advantages and disadvantages, and military application cases of fixed-wing, rotary-wing, hybrid, and swarm drones. It also discusses the development direction of drone technology, changes in military strategy, opportunities, and challenges. The results show that each type of drone plays a crucial role in various military operations such as reconnaissance, surveillance, strike, logistics, search, and rescue. With advancements in artificial intelligence, autonomous flight, and swarm technologies, the range of drone applications is expected to expand further. However, ensuring the safety and ethics of drone operations and establishing international norms have emerged as major challenges.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.34-45
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• 2013

Due to its self-configuring nature, the tactical mobile ad hoc network is used for communications between tactical units and the command and control center (CCC) in battlefields, where communication infrastructure is not available. However, when a tactical unit moves far away from the CCC or there are geographical constraints, the data link between two communicating nodes can be broken, which results in an invalid data route from the tactical units to CCC. In order to address this problem, in this paper we propose a hierarchical connectivity maintenance scheme, namely ADLCoM (Autonomous Data Link Connectivity Maintenance). In ADLCoM, each tactical unit has one or more GW (gateway), which checks the status of data links between tactical units. If there is a possibility of link breakage, GWs request ground or aerial unmanned vehicles to become a relay for the data link. The simulation results, based on tactical scenarios, show that the proposed scheme can significantly improve the network performance with respect to data delivery ratio.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.243-251
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• 2021

Real-Time Kinematic (RTK) is a phase-based differential GNSS technique and uses additional observations from permanent reference stations to mitigate or eliminate effects like atmospheric delays or satellite clocks and orbit errors. In particular, as the position accuracy required in the fields of autonomous vehicles and drones is gradually increasing, the demand for RTK-based precise navigation that can provide cm-level position is increasing. Recently, with the rapid growth of the open-source software market, the use of open-source software for building navigation system of unmanned vehicles, which is difficult to mount an expensive GNSS receivers, is gradually increasing. RTKLIB is an open-source software package that can perform RTK positioning and is widely used for research and education purposes. However, since the performance and stability of RTK algorithm of RTKLIB is inevitably inferior to that of commercial GNSS receivers, users need to verify whether RTKLIB can satisfy the navigation performance requirements of unmanned vehicles. Therefore, in this paper, the performance evaluation of the RTK positioning algorithm of RTKLIB was performed using GNSS observation data acquired in a dynamic environment. Therefore, in this paper, the RTK positioning performance of RTKLIB was evaluated using GNSS observation data acquired in a dynamic environment. Our results show that the current RTK algorithm of RTKLIB is not suitable for precise navigation of unmanned vehicles.

• The Journal of Korea Robotics Society
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• v.18 no.3
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.590-593
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• 2005

Unmanned Helicopter has several abilities such as vertical Take off, hovering, low speed flight at low altitude. Such vehicles are becoming popular in actual applications such as search and rescue, aerial reconnaissance and surveillance. These vehicles also used under risky environments without threatening the life of a pilot. Since a small unmanned helicopter is very sensitive to environmental conditions, it is generally known that the flight control is very difficult problems. The nonlinear adaptive fuzzy controller design procedure and its applications for altitude control of unmanned helicopter were described in the paper. This research was concentrated on describing the design methodologies of altitude controller design for small unmanned helicopter acquiring autonomous take off and vertical movement. The design methodologies and performance of the altitude controller were simulated and verified with an adaptive fuzzy controller. Throughout simulation results, I showed that the proposed adaptive controllers have enhanced control performance such as robustness, effectiveness and safety, in the altitude control of the unmanned helicopter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.988-995
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• 2008

A consensus-based feedback linearization method is proposed to maintain a specified time-varying geometric configuration for formation flying of multiple autonomous vehicles. In this approach, there exists no explicit leader in the team, and the proposed control strategy requires only the local neighbor-to-neighbor information between vehicles. The information flow topology between the vehicles is defined by Graph Laplacian matrix, and the formation flying can be achieved by the proposed feedback linearization with consensus algorithm. The stability analysis of the proposed controller is also performed via eigenvalue analysis for the closed-looop system. Numerical simulation is performed for rotary-wing type micro aerial vehicles to validate the performance of the proposed controller.