• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.15-22
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• 2019

In this paper, a global and local flight path system for autonomous flight of the UAV is proposed. The overall system is based on the ROS robot operating system. The UAV in-built computer detects obstacles through 2-D Lidar and generates real-time local path and global path based on VFH and Modified $RRT^*$-Smart, respectively. Additionally, a movement command is issued based on the generated path on the UAV flight controller. The ground station computer receives the obstacle information and generates a 2-D SLAM map, transmits the destination point to the embedded computer, and manages the state of the UAV. The autonomous UAV flight system of the is verified through a simulator and actual flight.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.13-23
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• 1996

When artificial potential field approach is used to avoid obstacle, the problem can be occurred in case that manipulator selects the path which across over an obstacle among paths. In thiscase manipulator can't reach the desired goal form obstacle. This problem is a case of structual local minimum. so this paper proposes the method to solve structual local minimum in this case. The method is that the manipulator goes via temporary goal. This paper proposes that visual region concept to select the temporary goal. The temporary goal is selected on the border of the visual region. To prove its effectiveness, two simulation examples are done by two link manipulator in two dimension and by three link manipulator in three dimension.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.91-97
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• 2002

This paper describes a heuristic search technique carrying out collision avoidance for Autonomous Underwater Vehicles(AUVs). Fuzzy relational products are used as the mathematical implement for the analysis and synthesis of relations between obstacles that are met in the navigation environment and available candidate nodes. In this paper, we propose a more effective evaluation function that reflects the heuristic information of domain experts on obstacle clearance, and an advanced heuristic search method performing collision avoidance for AUVs. The search technique adopts fuzzy relational products to conduct path-planning of intelligent navigation system. In order to verify the performance of proposed heuristic search, it is compared with $A^*$ search method through simulation in view of the CPU time, the optimization of path and the amount of memory usage.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.429-432
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• 2003

In this paper, a novel neural network approach is proposed for cleaning robot to complete coverage path planning with obstacle avoidance in stationary and dynamic environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location without any prior knowledge of the dynamic environment.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.66-72
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• 2010

In an autonomous multi-mobile robot environment, optimal path planning without collision which connects the beginning and ending point is essential and primary important. Many mobile robots should move autonomously without prior or given information about obstacles which are stationary or dynamic. Collision free optimal path planning for multi mobile robots is proposed in this paper. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner using potential field method selects the shortest path from each robot to its own target. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. To verify performance of this method, several simulation-based experimental are done and their results are discussed. These results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.623-629
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• 2018

In this paper, we propose a real-time obstacle detection and avoidance path generation algorithm for UAV. 2-D Lidar is used to detect obstacles, and the detected obstacle data is used to generate real-time histogram for local avoidance path and a 2-D SLAM map used for global avoidance path generation to the target point. The VFH algorithm for local avoidance path generation generates a real-time histogram of how much the obstacles are distributed in the vector direction and distance, and this histogram is used to generate the local avoidance path when detecting near fixed or dynamic obstacles. We propose an algorithm, called modified $RRT^*-Smart$, to overcome existing limitations. That generates global avoidance path to the target point by creating lower costs because nodes are checked whether or not straight path to a target point, and given arbitrary lengths and directionality to the target points when nodes are created. In this paper, we prove the efficient avoidance maneuvering through various simulation experiment environment by creating efficient avoidance paths.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1418-1425
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• 2003

In CAD systems, a surface to be machined is expressed by a series of curves, such as B-spline, Bezier and NURBS curves, which compose the surface and then in CAM systems the curves are divided into a large number of line or arc segments. These divided movement commands, however, cause many problems including their excessive size of NC data that makes almost impossible local adjustment or modification of the surface. To cope with those problems, the necessity of real-time curve or surface interpolators was embossed. This paper presents an efficient real-time tool-path generation method fur interpolation of NURBS surfaces in CNC machining. The proposed tool-path generation method is based on an improved iso-scallop strategy and can provide better precision than the existing methods. The proposed method is designed such that tool-path planning is easily managed in real-time. It proposed a new algorithm for regulation of a scallop height, which can efficiently generate tool-paths and can save machining time compared with the existing method. Through computer simulations, the performance of the proposed method is analyzed and compared with the existing method in terms of federate, total machining time and a degree of constraint on the scallop height.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.551-553
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• 2006

An autonomous navigation technology for the mobile robot is investigated in this paper. The proposed robot path planning algorithm employs the dynamic programming to find the optimal path. The algorithm finds the global optimal path through the local computation on the environmental map. Since the robot computes the new path at every point, it can avoid the obstacle successfully during the navigation. The experimental results of the robot navigation are included in this paper.