• 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 Korea Society for Simulation
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• v.16 no.1
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• pp.31-37
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• 2007

The importance of NPC's role in computer games is increasing. An NPC must perform its tasks by perceiving obstacles and other characters and by moving through them. It has been proposed to plan a natural-looking path against fixed obstacles by using a generalized visibility graph. In this paper we develop the execution module for an NPC to move efficiently along the path planned on the generalized visibility graph. The planned path consists of line segments and arc segments, so we define steering behaviors such as linear behaviors, circular behaviors, and an arriving behavior for NPC's movements to be realistic and utilize them during execution. The execution module also includes the collision detection capability to be able to detect dynamic obstacles and uses a decision tree to react differently according to the detected obstacles. The execution module is tested through the simulation based on the example scenario in which an NPC interferes the other moving NPC.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.365-373
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• 2023

Unmanned aerial vehicles are widely used in various fields, and real-time path replanning is a critical factor in enhancing the safety and efficiency of these devices. In this paper, we propose a real-time path replanning technique based on RRT* and LOSPO. The proposed technique first generates an initial path using the RRT* algorithm and then optimizes the path using LOSPO. Additionally, the optimized path can be converted into a trajectory that considers actual time and the dynamic limits of the aircraft. In this process, environmental changes and collision risks are detected in real-time, and the path is replanned as needed to maintain safe operation. This method has been verified through simulation-based experiments. The results of this paper make a significant contribution to the research on real-time path replanning for UAVs, and by applying this technique to various situations, the safety and efficiency of UAVs can be improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.15-20
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• 2024

Path planning for unmanned aerial vehicles (UAV) is crucial in avoiding collisions with obstacles in complex environments that include both static and dynamic obstacles. Path planning algorithms like RRT and A^* are effectively handle static obstacle avoidance but have limitations with increasing computational complexity in high-dimensional environments. Reinforcement learning-based algorithms can accommodate complex environments, but like traditional path planning algorithms, they struggle with training complexity and convergence in higher-dimensional environment. In this paper, we proposed a reinforcement learning model utilizing a cell decomposition algorithm. The proposed model reduces the complexity of the environment by decomposing the learning environment in detail, and improves the obstacle avoidance performance by establishing the valid action of the agent. This solves the exploration problem of reinforcement learning and improves the convergence of learning. Simulation results show that the proposed model improves learning speed and efficient path planning compared to reinforcement learning models in general environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.11
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• pp.730-742
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• 2014

In the case of On-demand routing protocol in cognitive radio ad-hoc networks, broadcasting of control packets may occur common control channel overload and packet collisions during the routing procedure. This situation is to increase the overhead of path finding and also limited to find the accurate and reliable path. Since reliable channel and path finding is restricted, path life time is shorten and path reliability is reduced. In this paper, we propose a new routing algorithm that reduces control channel overhead and increases path life time by considering the probability of appearance of primary user and channel status of neighbor nodes. Each node performs periodic local sensing to detect primary user signal and to derive primary user activity patterns. The probability of primary appearance on the current channel and the channel status can be obtained based on the periodic sensing. In addition, each node identifies the quality of the channel by message exchange through a common channel with neighbor nodes, then determines Link_Levels with neighbor nodes. In the proposed method, the Link Level condition reduces the number of control messages that are generated during the route discovery process. The proposed method can improve path life time by choosing a path through Path_Reliability in which stability and quality are weighted depending on the location. Through simulation, we show that our proposed algorithm reduces packet collisions and increases path life time in comparison with the traditional algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.3
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• pp.13-19
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• 2012

The fatalities rate for passenger vehicles, vans, and commercial vehicles is 1.23, 1.90 and 2.46 deaths per 10,000 registered vehicles, respectively. This shows that vans and commercial vehicles are vulnerable compare to passenger vehicles. To evaluate the crashworthiness of van and Light Truck Vehicle(LTV), we carried out frontal offset crash test at 64km/h, 40% overlap as per IIHS(Insurance Institute for Highway Safety). The test result show that LTV is very poor to protect occupant at frontal crash cause there is no safety system such as airbag and pretensioner and front end length(distance from front bumper to steering wheel) is short. One of the van rated as the lowest rating even it is equipped with airbag, cause its safety cage was collapsed during the test. This result shows that the structural integrity is very important in terms of occupant protection.

• Journal of the Korean Arthroscopy Society
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• v.14 no.1
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• pp.45-48
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• 2010

We report a case of an 85-year-old woman with tuberculous subdeltoid bursitis. Tubeculous bursitis without adjacent joint tuberculosis may occur any site but it is rare. It is common in bursae subjected to trauma like trochanteric, prepatellar, olecranon and so on. Because the clinical findings or physical examination of tuberculous subdeltoid bursitis are similar to rotator cuff disorder and the MRI or arthroscopic findings are similar to synovial diseases, careful differential diagnosis is necessary.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.435-442
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• 2000

In the world of mobile agents, security aspects are extensively being discussed, with strong emphasis on how agents can be protected against malicious hosts and vice versa. This paper discusses methods for protecting an agent's route information from being misused by sites on route interested in gaining insight into the profile of the agent's owner or in obstructing the owner's original goal. Our methods provide visited sites with just a minimum of route information, but on the other hand allow sites to detect modifying attacks of preceding sites. Though, under noncolluding attacks, all methods presented provide a similar level of protection, the performance and the points of time differ when an attack can be detected.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.329-334
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• 2002

For the testability, this paper proposed the algorithm at autonomous synthesis which includes the data path structure as the self testing as possible on high level synthesis method when VHDL, coding is used in the system design area. In the proposed algorithm of this paper, MUXs and registers are assigned to the data path of designed system. And the designed data path could be mapped the H/W specification of described VHDL coding to the testable library. As a results, it was mapped H/W to the assign algorithm that is minimized MUX and the registers in collision graph.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.520-524
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• 2007

제한된 전지를 사용하는 노드들로 이루어진 이동 애드혹 네트워크 환경에서 멀티 홉 간의 에너지 효율적인 경로 설정은 매우 중요한 이슈이다. 이러한 문제를 해결하기 위해서 본 논문에서는 이동 애드혹 네트워크 환경에서 자주 사용되는 라우팅 프로토콜 중 하나인 AODV(Ad-hoc On-demand Distance Vector) 라우팅 프로토콜을 기반으로, 네트워크 계층과 MAC계층의 자원을 크로스 레이어 기법을 활용하여 에너지 효율적인 크로스 레이어 라우팅 프로토콜을 제안한다. 네트워크 계층에서의 이웃노드에 관한 상태 정보를 크로스 레이어 기법을 활용하여 MAC 계층의 back-off time을 적절히 조절함으로써 프레임의 충돌을 줄이고, 패킷의 경로를 설정하는데 있어서 신뢰성과 효율성을 부여하기 위한 방법으로 MAC계층의 자원을 활용하여 얻은 Collision-Level을 사용한다. 또한 Collision Level은 패킷 경로 선택에 사용되는 지연시간을 적응성 있게 줄이는 자원으로 사용된다.