• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.4
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• pp.106-115
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• 1994

This paper presents the design of a technology mapping system for optimizing delays of combinational and synchronous sequential logic circuits. The proposed system performs delay optimization for combinational logic circuits by remapping, buffering, and gate merging methods through the correct delay calculation in which the loading values are considered. To get time optimized synchronous sequential circuits, heuristic algorithms are proposed. The proposed algorithms reallocate registers by considering the critical path characteristics. Experimental results show that the proposed system produces a more optimized technology mapping for MCNC benchmarks compared with mis-II.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.293-298
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• 1993

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.138.5-138
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• 2001

The autonomous robot has the ability of obstacle avoidance and target tracking with some manufactured information. In this paper, it is shown that autonomous mobile robot can avoid fixed obstacles using the map made before and the fuzzy controller is adopted with the global path planing and the local path planing when the robot navigates. With that map sensor, information will be used when an autonomous robot navigates. This paper proves that robot can navigate through optimized route and keep the stable condition.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.29-32
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• 2002

In this paper the wheeled mobile robot is studied. The kinematic and dynamic modeling of the robot is presented via LPD(Linear Parameter Dependent) framework. A path-planning algorithm which is optimized in the sense of robot mobility and distance is presented. And by using PI controller we show that the presented algorithm and model is work very well in the computer simulation and experiment.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.263-267
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• 2006

The path of a flapping airfoil during upstroke and down-stroke is optimized for maximum thrust and propulsive efficiency. The periodic flapping motion in combined pitch and plunge is described using Non-Uniform B-Splines(NURBS). A gradient based algorithm is employed for optimization of the NURBS parameters. Unsteady, low speed laminar flows are computed using a Navier-Stokes solver in a parallel computing environment based on domain decomposition. It is shown that the thrust generation is significantly improved in comparison to the sinusoidal flapping motion. For a high thrust generation, the airfoil stays at a high effective angle of attack for short durations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.76-90
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• 2010

Location Service is required in position-based routing for VANET to provide position information. We propose Grid-based Location service spot(GLSS) scheme for optimized routing path to improve accessibility and load balance in location service. Specific area is defined as Location service spot(LSS) on each grid in this scheme, and all nodes in the grid geocast its location update message and location request message to each LSS. Location request messages are flooded throughout LSSs, location reply messages establish optimized route from the source grid to the destination grid. We evaluated GLSS which establishes optimized route on the grid comparing GPSR in consideration of road condition and geographical features.

• Journal of Distribution Science
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• v.13 no.6
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• pp.11-15
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• 2015

Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

• Journal of Drive and Control
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• v.21 no.1
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• pp.46-52
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• 2024

The advancement of autonomous driving technology has heightened the importance of Autonomous Mobile Robotics (AMR) within smart factories. Notably, in tasks involving the transportation of heavy objects, the consideration of weight in route optimization and path planning has become crucial. There is ongoing research on local path planning, such as Dijkstra, A^*, and RRT^*, focusing on minimizing travel time and distance within smart factory warehouses. Additionally, there are ongoing simultaneous studies on route optimization, including TSP algorithms for various path explorations and on minimizing energy consumption in mobile robotics operations. However, previous studies have often overlooked the weight of the objects being transported, emphasizing only minimal travel time or distance. Therefore, this research proposes route planning that accounts for the maximum payload capacity of mobile robotics and offers load-optimized path planning for multi-destination transportation. Considering the load, a genetic algorithm with the objectives of minimizing both travel time and distance, as well as energy consumption is employed. This approach is expected to enhance the efficiency of mobility within smart factories.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.12
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• pp.1036-1043
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• 2016

In this paper, an analysis about the elevation angle accuracy degradation of an APAR(Airport Precision Approach Radar) due to the multi-path effect using a phased array antenna was performed. An APAR installed around a runway of airport will be continuously affected in a runway surface of the fixed environment. In this paper, an analysis about the elevation angle accuracy degradation of APAR due to the multi-path effect of runway surface was conducted through a calculation of monopluse slope and sum/difference beam pattern analysis of array antenna. Also, a difference pattern for monopulse to minimize this degradation was optimized in an appropriate configuration to improve a elevation angle accuracy. Finally, a degree of improvement of elevation angle accuracy was confirmed by calculating a monopulse slope including the ground reflection after applying optimized difference patterns of array antenna.

• 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.