• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.98-106
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• 1991

Future generation of robots will be considerably more autonomous than present robotic systems. The main objective of research on theoretical problems in robotics is to endow robotics system with basic capabilities they will need to operate in an intelligent and autonomous manner. This paper discusses the problem of collision free movement of robot manipulator. It is formulated in path planning with obstacle avoidance expressed in the term of the distance between convex shapes in the three dimensional space. The examples are given to illustrate the main feature of the method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.147-151
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• 1991

In this paper a time-optimal path planning scheme for the multiple robot manipulators will be proposed by using hopfield neural network. The time-optimal path planning, which can allow multiple robot system to perform the demanded tasks with a minimum execution time and collision avoidance, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to rearrange the problem as MTSP(Multiple Travelling Salesmen Problem) and then apply the Hopfield network technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning of the multiple robots by using Hopfield neural network. The effectiveness of the proposed method is demonstrated by computer simulation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.99-102
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• 1996

Research regarding the Autonomous Distributed & Cooperated System has not yet been defined because we need to apply the interdisciplinary approach before so. In this paper, we use a clear definition, compare characteristics of the Autonomous Distributed & Cooperated System and examine the possibility of an actualization through path planning of Autonomous AGV. We propose a new algorithm about the generation method of a moving path at the first stage and a cooperative action generation for a collision avoidance. Lastly, we performed simulation analysis of these two in order to confirm efficiency.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.1-8
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• 2008

Automatic parking assist system is one of the key technologies of the future automobiles. Control problem of a car-like vehicle is not easy due to the nonholonomic constraints. In this paper, a practical solution for planning a car-parking path is proposed according to the proposed motion space (M-space) approach. The M-space is the extension of the conventional configuration space (C-space). A collision-free, nonholonomic feasible path can be directly computed by the M-space conversion and a back-propagation of reachable regions from the goal. The proposed planning scheme provide not a single solution, but also a candidate solution set, therefore, optimization of the parking path can be easily carried out with respect to performance criteria such as safety, maneuvering, and so on. Presented simulation results clearly show that the proposed scheme provides various practical solutions.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.63-74
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• 2009

In 2005, Wang et al. discovered devastating collision attacks on the main hash functions from the MD4 family. After the discovery of Wang, many analysis results on the security of existing hash-based cryptographic schemes are presented. At CRYPTO'07, Fouque, Leurent and Nguyen presented full key-recovery attacks on HMAC/NMAC-MD4 and NMAC-MD5[4]. Such attacks are based on collision attacks on the underlying hash function, and the most expensive stage is the recovery of the outer key. At EUROCRYPT'08, Wang, Ohta and Kunihiro presented improved outer key recovery attack on HMAC/NMAC-MD4, by using a new near collision path with a high probability[2]. This improves the complexity of the full key-recovery attack on HMAC/NMAC-MD4 which proposed by Fouque, Leurent and Nguyen at CRYPTO'07: The MAC queries decreases from $2^{88}$ to $2^{72}$, and the number of MD4 computations decreases from $2^{95}$ to $2^{77}$. In this paper, we propose improved outer key-recovery attack on HMAC/NMAC-MD4 with $2^{77.1246}$ MAC queries and $2^{37}$ MD4 computations, by using divide and conquer paradigm.

• Journal of IKEEE
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• v.13 no.2
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• pp.150-158
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• 2009

For the autonomous movement, the optimal path planning connecting between current and target positions is essential, and the optimal path of mobile robot means obstacle-free and the shortest length path to a target position. Many actual mobile robots should move without any information of surrounded obstacles. Thus, this paper suggests new methods of path planning and obstacle avoidment, suitable in unknown environments. This method of path planning always tracks the local target expected as the optimal one, and the result of continuous tracking becomes the first generated moving path. This path, however, do not regard the collision with obstacles. Thus, this paper suggests a new method of obstacle avoidance resembled with the Potential Field method. Finally, a simulation confirms the performance and correctness of the path planning and obstacle avoidance, suggested in this paper.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.250-259
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• 2021

Path planning is one of the important technologies for automated parking. It requires to plan a collision-free path considering the vehicle's kinematic constraints such as minimum turning radius or steering velocity. In a complex parking lot, Rapidly-exploring Random Tree^* (RRT^*) can be used for planning a parking path, and Reeds-Shepp or Hybrid Curvature can be applied as a tree-extension method to consider the vehicle's constraints. In this case, each of these methods may affect the computation time of planning the parking path, path-tracking error, and parking success rate. Therefore, in this study, we conduct comparative analysis of two tree-extension functions: Reeds-Shepp (RS) and Hybrid Curvature (HC), and show that HC is a more appropriate tree-extension function for parking path planning. The differences between the two functions are introduced, and their performances are compared by applying them with RRT^*. They are tested at various parking scenarios in simulation, and their advantages and disadvantages are discussed by computation time, cross-track error while tracking the path, parking success rate, and alignment error at the target parking spot. These results show that HC generates the parking path that an autonomous vehicle can track without collisions and HC allows the vehicle to park with lower alignment error than those of RS.

• Spatial Information Research
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• v.15 no.4
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• pp.363-370
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• 2007

This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..