• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.156-161
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• 2020

In an environment that operates multiple UAVs, the use of a decentralized task allocation algorithm has more robustness from a single failure of UAV on the mission because there is no central command center. In addition, UAVs have situational awareness and redistribute tasks among themselves, which can expand the mission range. The use of multiple UAVs in a mission has increased as the agent hardware has decreased in size and cost. The decentralized mission-planning algorithm has the advantages of a larger mission range and robustness to a single failure during the mission. This paper extended the type of mission the uses CBBA, which is the most well-known decentralized task allocation algorithm, to the point mission and en-route mission. This will describe the real mission situation that has the purpose of surveillance. A Monte-Carlo simulation was conducted in the case of multiple agents in the task-rich environment, and the global rewards of each case were compared.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.2
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• pp.159-166
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• 2020

In this paper, we propose a heterogenous mission allocation technique for multi-UAV system based on discrete event modeling. We model a series of heterogenous mission creation, mission allocation, UAV departure, mission completion, and UAV maintenance and repair process as a mathematical discrete event model. Based on the proposed model, we then optimize the number of UAVs required to operate in a given scenario. To validate the optimized number of UAVs, the simulations are executed repeatedly, and their results are analyzed. The proposed mission allocation technique can be used to efficiently utilize limited UAV resources, and allow the human operator to establish an optimal mission plan.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.988-996
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• 2012

This paper presents a distributed task assignment algorithm for the suppression of enemy air defense (SEAD) mission of heterogeneous UAVs, based on the consensus-based bundle algorithm (CBBA). SEAD mission can be modeled as a task assignment problem of multiple UAVs performing multiple air defense targets, and UAVs performing SEAD mission consist of the weasel for destruction of enemy's air defense system and the striker for the battle damage assessment (BDA) or other tasks. In this paper, a distributed task assignment algorithm considering path-planning in presence of terrain obstacle is developed for heterogeneous UAVs, and then it is applied to SEAD mission. Through numerical simulations the performance and the applicability of the proposed method are tested.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.427-436
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• 2010

This paper deals with a task assignment problem of multiple UAVs performing multiple tasks on multiple targets. The task assignment problem of multiple UAVs is a kind of combinatorial optimization problems such as traveling salesman problem or vehicle routing problem, and it has NP-hard computational complexity. Therefore, computation time increases as the size of considered problem increases. To solve the problem efficiently, approximation methods or heuristic methods are widely used. In this study, the problem is formulated as a mixed integer linear program, and is solved by a mixed integer linear programming and a genetic algorithm, respectively. Numerical simulations for the environment of the multiple targets, multiple tasks, and obstacles were performed to analyze the optimality and efficiency of each method.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.78-85
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• 2023

For Multi-UAV systems, a task allocation could be a key factor to determine the capability to perform a task. In this paper, we proposed a task allocation method based on genetic algorithm for minimizing makespan and satisfying various constraints. To obtain the optimal solution of the task allocation problem, a huge calculation effort is necessary. Therefore, a genetic algorithm-based method could be an alternative to get the answer. Many types of UAVs, tasks, and constraints in real worlds are introduced and considered when tasks are assigned. The proposed method can build the task sequence of each UAV and calculate waiting time before beginning tasks related to constraints. After initial task allocation with a genetic algorithm, waiting time is added to satisfy constraints. Multiple numerical simulation results validated the performance of this mission planning method with minimized makespan.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.451-453
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• 2004

오래 전부터 많은 컴퓨팅 시스템에서 기분적으로 제공되어지는 원리인 임무분리는 중대한 업무를 둘 이상의 사용자에게 나누어줌으로써 단독 사용자가 시스템을 손상시키는 것을 막도록 하는 것이 목적이다. 역할기반 접근통제에서 임무분리 원리를 제공하는 종류로는 정적 임무분리, 동적 임무분리, 기능적 임무분리, 객체기반 임무분리 등이 있다. 여기서 우리는 정적 임무분리를 만족시키는 모델로서 상호 배제 역할 쌍을 이용한 모델과 역할유형을 이용한 모델 그리고 상호 무관 역할 쌍을 이용한 모델을 제안한다

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.59-66
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• 2011

In this paper, a method to allocate a submarine search mission to an ASW(Anti-Submarine Warfare) helicopter is proposed. The aim of the proposed method is to increase the submarine detection capability. For this purpose, we modeled the behaviors that the ASW helicopter conduct during the search mission, and the relations between the behaviors are also modeled. To measure quantitatively the effectiveness of ASW search mission, the measure of effectiveness(MOP) is defined. Scenarios are designed to analyze the effectiveness utilizing the ASW mission model. We conducted simulations applying the designed scenarios and some parameters concerned with the friendly ship and the enemy submarine interacting each other in the ASW missions. We analyzed the result of simulation depending on the dipping interval and the pattern of dipping positions in the situation that the helicopter operates for a long time and should resupply several times on the friendly ship. From the analyzed data, we suggested the practical value of ratio between the detectable range of the sonar and the dipping interval to improve the effectiveness of ASW mission.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.197-202
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• 2014

In order to operate multiple UAVs for multiple tasks efficiently, we need a task allocation algorithm with minimum cost, i.e.,total moving distance required to accomplish the whole mission. In this paper, we have proposed the MCBAA (Modified Consensus Based Auction Algorithm) which can be suitably applied to the operation of multiple UAVs. The key idea of proposed algorithm is to minimize sum of distance from current location of agents to location of tasks based on the conventional CBAA. Several simulation test performed on three UAV agents with multiple tasks demonstrates the overall efficiency both in time and total distance.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.56-63
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• 2024

As the safety of unmanned vehicles continues to improve, their usage in urban environments, which are full of obstacles such as buildings, is expected to increase. When numerous unmanned vehicles are operated in such environments, an algorithm that takes into account mutual collision avoidance, as well as static and dynamic obstacle avoidance, is necessary. In this paper, we propose an algorithm that handles task assignment and path planning. To efficiently plan paths, we construct a grid-based map and derive the paths from it. To enable quick re-planning in dynamic environments, we focus on reducing computational time. Through simulation, we explain obstacle avoidance and mutual collision avoidance in small-scale problems and confirm their performance by observing the entire mission completion time (Makespan) in large-scale problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.558-565
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• 2021

The Republic of Korea Navy has deployed naval fleets in the East, West, and South seas to effectively respond to threats from North Korea and its neighbors. However, it is difficult to allocate proper missions due to high uncertainties, such as the year of introduction for the ship, the number of mission days completed, arms capabilities, crew shift times, and the failure rate of the ship. For this reason, there is an increasing proportion of expenses, or mission alerts with high fatigue in the number of workers and traps. In this paper, we present a simulation model that can optimize the assignment of naval vessels' missions by using a continuous time absorbing Markov chain that is easy to model and that can analyze complex phenomena with varying event rates over time. A numerical analysis model allows us to determine the optimal mission durations and warship quantities to maintain the target operating rates, and we find that allocating optimal warships for each mission reduces unnecessary alerts and reduces crew fatigue and failures. This model is significant in that it can be expanded to various fields, not only for assignment of duties but also for calculation of appropriate requirements and for inventory analysis.