• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.389-389
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• 2000

The number of automobiles is rapidly increasing , as are the importance of the car as a way of transportation, and the variety of its uses. In these surroundings, a safety, one of the primary factors which must be considered in automotive engineering, demands a system that aids the driver's vision and perception. In this point of view, development of the more promoted system that complement the existing passive method which relies on just man's ability is the important issue of the advanced traffic system including ITS. In this paper, we provide an algorithm and implementation of a control system that warns the collisions ahead and avoids this situation, using informations about the host-car, target-car and surroundings. The warning is made by an algorithm that decides the degree of safely. With this degree of safely, the controller automatically controls a vehicle's speed to a proper level.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1327-1332
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• 2018

An AGV(Automated Guided Vehicle) where is running on production automated system is related efficiency of production system similarly. On previous study proposed a path collision avoidance algorithms using shortest path of AGV. Running time about loading and unloading with shortest path of AGV is important factor to decide the production system efficiency. In this paper, we propose a method of shortest path and shortest time. Also propose the decision making method of collision avoidance position for setup a shortest runway for next command. To do verify the proposed method consist a simulation for AGV. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively the performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1163-1170
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• 2008

A mission scheduling optimization algorithm according to the purpose of satellite operations is developed using genetic algorithm. Satellite mission scheduling is making a timetable of missions which are slated to be performed. It is essential to make an optimized timetable considering related conditions and parameters for effective mission performance. Thus, as important criterions and parameters related to scheduling vary with the purpose of satellite operation, those factors should be fully considered and reflected when the satellite mission scheduling algorithm is developed. The developed algorithm in this study is implemented and verified through a comprehensive simulation study. As a result, it is shown that the algorithm can be applied into various type of the satellite mission operations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.48-57
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• 2010

A comparison of two kinds of scheduling optimization algorithms is presented in this paper. As satellite control and operation techniques have been developed, satellite missions became more complicated and overall quantity of missions also increased. These changes require more specific consideration and a huge amount of computation for the satellite mission scheduling. Therefore, it is a good strategy to make a scheduling optimization algorithm for the efficient satellite mission scheduling operation. In this paper, two kinds of scheduling optimization algorithms are designed with tabu-search algorithm and genetic algorithm respectively. These algorithms are applied for the same mission scenario and the results of each algorithm are compared and analyzed.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.103-111
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• 2010

This paper proposes an efficient data transmission strategy using adaptive-tier low transmission power schedule in a TDMA-based ad hoc MAC protocol. Since the network resource of ad hoc networks has the characteristic of reassignment due to the multiple interferences and the contention-based limited wireless channel, the efficient time slot assignment and low power transmission scheme are the main research topics in developing ad hoc algorithms. Based on the proposed scheme of interference avoidance when neighbor clusters transmit packets, this paper can minimize the total energy dissipation and maximize the utilization of time slot in each ad hoc node. Simulation demonstrates that the proposed algorithm yields 15.8 % lower energy dissipation and 4.66% higher time slot utilization compared to the ones of two-tier conventional energy dissipation model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.139-142
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• 2009

RFID(Radio Frequency IDentification) technology is an automatic identification method using radio frequencies between RFID reader which collects the information and tag which transmits the information. RFID technology develops passive RFID which transmit the only ID to active RFID which transmit the additional information such as sensing information. However, ISO/IEC 18000-7 as active RFID standard has a problem which cannot use multiple channel. To solve this problem, we use the 2.4GHz bandwidth technology and we propose the dynamic channel allocation method which can efficiently allot a channel. we show the operation of the dynamic channel allocation method through design and implement with CC2500DK of Taxas Instrument.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.493-498
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• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.355-362
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• 2009

In this paper, we present a framework for managing group behaviors in multi-agent swarm systems. The framework explores the benefits by dynamic associations with the proposed artificial potential functions to realize complex swarming behaviors. A key development is the introduction of a set of flocking by dynamic association (DA) algorithms that effectively deal with a host of swarming issues such as cooperation for fast migration to a target, flexible and agile formation, and inter-agent collision avoidance. In particular, the DA algorithms employ a so-called systematic singular association (SSA) rule for fast migration to a target and compact formation through inter-agent interaction. The resulting algorithms enjoy two important interrelated benefits. First, the SSA rule greatly reduces time-consuming for migration and satisfies low possibility that agents may be lost. Secondly, the SSA is advantageous for practical implementations, since it considers for agents even the case that a target is blocked by obstacles. Extensive simulation presents to illustrate the viability and effectiveness of the proposed framework.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.352-360
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• 2019

This paper proposes a docking assessment algorithm for an autonomous underwater vehicles (AUVs) with sensor uncertainties. The proposed algorithm consists of two assessments, state assessment and probability assessment. The state assessment verifies the reachability by comparing forward distance to the docking station with expected distance to reach same depth as the docking station and necessity for correcting its route by comparing calculated inaccessible areas based on turning radius of the AUV to position of the docking station. When the AUV and the docking station is close enough and the state assessment is satisfied, the probability assessment is conducted by computing success probability of docking based on the direction angle, relative position to the docking station, and sensor uncertainties of the AUV. The final output of the algorithm is decided by comparing the success probability to threshold whether to try docking or to correct its route. To verify the validation of the suggested algorithm, the scenario that the AUV approaches to the docking station is implemented through Matlab simulation.