• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.3
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• pp.143-150
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• 2012

In this paper, we introduce an intelligent quadruped walking robot that can perform stable walking and a couple of intelligent behaviors. The developed robot has two sets of ultrasonic sensors and six sets of infrared sensors and can perform obstacle avoidance by detecting obstacles and estimating the distances and directions of those obstacles. The robot also has a stereo camera and can paly soccer by detecting a ball and estimating the 3 dimensional coordinates of the ball. In performing those intelligent behaviors, the robot needs to have the capability of generating its walking patterns, solving the inverse kinematics problem, and interfacing several sensors in realtime. Therefore we designed a hierarchical controller that consists of a main controller and an auxiliary controller. The main controller is a 32-bit DSP that can perform fast floating-point opertaion and the auxiliary one is a 8-bit micro-controller. We showed that the developed quadruped walking robot successfully perform those intelligent behaviors through experiments.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.132-145
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• 2008

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.105-110
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• 1999

This paper presents a local obstacle avoidance method for indoor mobile robots using Lane method and velocity Space Command approach. The method locates local obstacles using the information form multi-sensors, such that ultrasonic sensor array and laser scanning sensor. The method uses lane method to determine optimum collision-free heading direction of a robot. Also, it deals with the robot motion dynamics problem to reduce some vibration and guarantee fast movement as well. It yields translational and rotational velocities required to avoid the detected obstacles and to keep the robot heading direction toward goal location as close as possible. For experimental verification of the method, a mobile robot driven by two AC servo motors, equipped with 24 ultrasonic sensor array and laser scanning sensor navigates using the method through a corridor cluttered with obstacle.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.5
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• pp.551-561
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• 1992

A neural optimization network and fuzzy rules are proposed to control the redundant robot manipulators in an environment with obstacle. A neural optimization network is employed to solve the optimization problem for resolved motion control of redundant robot manipulators in an environment with obstacle. The fuzzy rules are proposed to determine the weights of neural optimization networks to avoid the collision between robot manipulators and obstacle. The inputs of fuzzy rules are the resultant distance and change of the distance and sum of the changes by differential motion of each joint. And the output of fuzzy rules is defined as the capability of collision avoidance of joint differential motion. The weightings of neural optimization networks are adjusted according to the capability of collision aboidance of each joint. To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot of the planar type with three degrees of freedom.

• Journal of the Korean Mathematical Society
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• v.56 no.1
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• pp.239-263
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• 2019

The $Calder{\acute{o}}n$-Zygmund type estimate is proved for elliptic obstacle problems in bounded non-smooth domains. The problems are related to divergence form nonlinear elliptic equation with measurable nonlinearities. Precisely, nonlinearity $a({\xi},x_1,x^{\prime})$ is assumed to be only measurable in one spatial variable $x_1$ and has locally small BMO semi-norm in the other spatial variables x', uniformly in ${\xi}$ variable. Regarding non-smooth domains, we assume that the boundaries are locally flat in the sense of Reifenberg. We also investigate global regularity in the settings of weighted Orlicz spaces for the weak solutions to the problems considered here.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.65-73
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• 2024

This paper presents a path planning optimization model for the engineering units to install obstacles in the shortest time during wartime. In a rapidly changing battlefield environment, engineering units operate various engineering obstacles to fix, bypass, and delay enemy maneuvers, and the success of the operation lies in efficiently planning the obstacle installation path in the shortest time. Existing studies have not reflected the existence of obstacle material storage that should be visited precedence before installing obstacles, and there is a problem that does not fit the reality of the operation in which the installation is continuously carried out on a regional basis. By presenting a Mixed Integrer Programming optimization model reflecting various constraints suitable for the battlefield environment, this study attempted to promote the efficient mission performance of the engineering unit during wartime.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1040-1045
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• 1991

An approach to time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in Cartesian space and in joint space. To deal with the time-varying obstacles, view-time is introduced. A view-time is the time interval viewing the time-varying obstacles to model equivalent stationary obstacles. For the analysis of the properties of the view-time, avoidability measure is defined as a measure of easiness for a robot to avoid obstacles. Based on the properties, a motion planning strategy to avoid time-varying obstacles is derived. An application of the strategy to the collision-free motion planning of two SCARA robots and the simulation on the application are given.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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• pp.269-276
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• 2014

In recent, autonomous navigation techniques to avoid obstacles have been studied by using unmanned aircraft vehicles(UAVs) since the increment of UAV's interest and utilization. Particularly, autonomous navigation based UAVs are utilized in several areas such as military, police, media, and so on. However, there are still some problems to avoid obstacle when UVAs perform autonomous navigation. For instance, the UAV can not forward in the corner of corridors even though it utilizes the improved vanish point algorithm that makes an autonomous navigation system. Therefore, in this paper, we propose an obstacle avoidance technique based on immune algorithm for autonomous navigation of Quadrotor. The proposed algorithm is consisted of two steps such as 1) single color discrimination and 2) multiple color discrimination. According to the result of experiments, we can solve the previous problem of the improved vanish point algorithm and improve the performance of autonomous navigation of Quadrotor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.249-254
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• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.