• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.184-184
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• 2003

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1455-1463
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• 1990

In this study the feasibility of a dynamic gait for a given quadruped walking robot is investigated through a computer simulation of the walking with certain drivings of the actuators. Two planar inverted pendulums are used to represent the dynamic model of the leg of the walking robot. It's gait motion is assumed to be periodic and symmetric between left and right sides only with half cycle delay. The dynamics of the walking robot is simplified by introducing two virtual legs to produce two planar inverted pendulums in two orthogonal planes and on the basis that certain legs in pair act as one. The feasibility of the dynamic gait motion is established from the following two necessary conditions:(1) The position and velocity of a foot must satisfy the stroke and velocity requirements.(2) The gait motion should be periodic without falling down. The gait feasibility test was applied to a walking robot design showing the specific acceptable speed range of the robot in trot. Also it showed that the higher body height may produce the faster trot gait.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.45-52
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• 2001

This paper presents a study on the position tracking control of a robot system on the uncertain elastic base. The elastic bathe is a nonholonomic system but it can be changed into holonomic system, which is much easier to analyze, by modeling an elastic base as a virtual robot that has passive joints. Also, Jacobian operators, which represent the overall robot system including base movement, are defined and applied to the changed model. However, because base movements are not known, the exact Jacobian operators can＇t be estimated. The control algorithm proposed is that uses only Jacobians of a real robot as approximate Jacobian operators. Therefore the approximate Jacobian operators compensate the measured errors from external sensors. The proposed control strategy is evaluated by the simulation and experiment of a single-axis robot system on the elastic base.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.51-58
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• 2006

Virtual Manufacturing is a powerful methodology for developing a new product, new equipment and new production system. It enables the checking errors in design before production. This paper is a case study of virtual manufacturing in an excavator factory. The final welding operations of the boom and the rotating table of upper body are selected for application. 3D models of parts and fixtures are developed with $CATIA^{(R)}$ and 3D simulation models are developed with $IGRIP^{(R)}$. These models are used for verifying the design of fixture and for the motion design of robot. As a result, the manual welding systems are replaced by automatic systems and many design errors are corrected in the design phase, which reduces the developing cost and time.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.249-252
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• 2007

This study shows possibility of Matlab and LabVIEW integration for controlling of robot's manipulator. Examined approach can be used for control of complex system with intelligent control capability. Instance of Robotic System controller is described in details. Structure of control system is divided into three parts Virtual Instrument of LabVIEW, MatLab Script for solving and Matlab Simulink model for visualizing, which are explained separately. In addition, used neglects are explained and founded.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.254-259
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• 1992

In this paper, we propose an optimal method for the tracking a trajectory of the end-effector of flexible robot arms with multiple joints. The proposed method finds joint trajectories and joint torques necessary to produce the desired end-effector motion of flexible manipulator. In inverse kinematics, optimized joint trajectories are computed from elastic equations. In inverse dynamics, joint torques are obtained from the joint equations by using the optimized joint trajectories. The equations of motion using finite element method and virtual work principle are employed. Optimal control is applied to optimize joint trajectories which are computed in inverse kinematics. The simulation of flexible planner manipulator is presented.

• Journal of Drive and Control
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• v.17 no.1
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• pp.44-50
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• 2020

For the requirement of accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Because of the complexity of humanoid robot dynamics, the TDC (time-delay control) is practical because it does not require a dynamic model. However, there occurs a considerable error due to discontinuous non-linearities. To solve this problem, the TDC-FLC (fuzzy logic compensator) is applied to humanoid robots. The applied controller contains three factors: a TDE (time-delay estimation) factor, a desired error dynamic factor, and FLC to suppress the TDE error. The TDC-FLC is easy to execute because it does not require complicated humanoid dynamic calculations and the heuristic fuzzy control rules are intuitive. TDC-FLC is implemented on the whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the TDC-FLC for humanoid robots.