• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.2
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• pp.114-123
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• 2017

This paper introduces a novel obstacle-climbing robot that moves on the facade of buildings and its climbing mechanism. A winch system set on the top of the building makes the vertical motion of the robot while it climbs obstacles that protrude from the wall surface. The obstacle-climbing robot suggested in this research is composed of a main platform and three modular climbing units. Various sensors installed on each climbing unit detect the obstacles, and the robot controller coordinates the three units and the winch to climb the obstacles using the obstacle-climbing mechanism. To evaluate the performance of the developed robot prototype, a test bed, which consists of an artificial wall and an obstacle, was manufactured. The obstacle size and the time required to climb the obstacle were selected as the performance indices, and extensive experiments were carried out. As a result, it was confirmed that the obstacle-climbing robot can climb various-sized obstacles with a reasonable speed while it moves on the wall surface.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2024-2029
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• 2005

In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. In order to achieve high speed and safe navigation, a robot collects environmental information. A robot empirically memorizes locations of high risk due to the abrupt appearance of dynamic obstacles. After collecting sufficient data, a robot navigates in high speed in safe regions. This fact implies that the robot accumulates location dependent environmental information and the robot exploits its experiences in order to improve its navigation performance. This paper proposes a computational scheme how a robot can distinguish regions of high risk. Then, we focus on velocity control in order to achieve high speed navigation. The proposed scheme is experimentally tested in real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation. Although the scope of this paper is limited to the velocity control in order to deal with unexpected obstacles, this paper points out a new direction towards the intelligent behavior control of autonomous robots based on the robot's experience.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.1
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• pp.41-48
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• 2013

In this work, 4-DOF ER haptic master is proposed and integrated with a slave robot for minimally invasive surgery(MIS). Using a controllable ER fluid, the haptic master can generate a repulsive force/torque with the 4-DOF motion. For realization of master-slave robot system, the motion command of the haptic master is realized by slave surgery robot. In order to follow the 4-DOF motion of the haptic master, novel mechanism of slave surgery robot with gimbal joint is devised. Accordingly, the haptic master-slave robot system is established by incorporating the slave robot with the haptic master device in which the desired repulsive force/torque and position are transferred to each other via wireless communications. In order to obtain the desired force/torque and position trajectories, tracking controllers for haptic master and slave robot are designed and implemented, respectively. It has been demonstrated that the desired effective torque tracking control performance is well achieved using the proposed haptic master-slave robot system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.421-427
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• 2012

In this work, 4 DOF ER haptic master is proposed and integrated with a slave robot for minimally invasive surgery (MIS). Using a controllable ER fluid, the haptic master can generate a repulsive force/torque with the 4-DOF motion. For realization of master-slave robot system, the motion command of the haptic master is realized by slave surgery robot. In order to follow the 4 DOF motion of the haptic master, novel mechanism of slave surgery robot with gimbal joint is devised. Accordingly, the haptic master-slave robot system is established by incorporating the slave robot with the haptic master device in which the desired repulsive force/torque and position are transferred to each other via wireless communications. In order to obtain the desired force/torque and position trajectories, tracking controllers for haptic master and slave robot are designed and implemented, respectively. It has been demonstrated that the desired effective torque tracking control performance is well achieved using the proposed haptic master-slave robot system.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.155-161
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• 2019

We introduces a mobile robot that can navigate on a power transmission line arranged in bundled conductors. The designs of the proposed robot are performed for navigation on bundled conductors, and the navigation method for bundled conductors and obstacle avoidance are presented. The robot consists of 13 degrees of freedom (DOF) with a symmetrical structure for the left and right parts, including the four wheel joints. The navigation method is designed using a combination of three motion primitives such as linear motion of counterbalancing box, linear motion of robot arm, and rotational motion of wheel part. To examine the performance of the proposed robot, navigation simulations are conducted using $ADAMS^{TM}$. The robot navigations were simulated on obstacle environments that consisted of two- and four-conductor bundles. Based on the simulation results, the performance of the proposed robot was reviewed through the analysis of the trajectories of end-effectors. We confirmed that the proposed robot was capable of achieving optimal navigation on bundled conductors that included obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1249-1255
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• 2004

A new parameter adaptation scheme for RBF Neural Network (NN) has been developed in this paper. Even though the RBF Neural Network (NN) based controllers are robust against both un-modeled dynamics and external disturbances, the performance is not satisfactory for a fast and precise mobile robot. To improve the tracking performance as well as robustness, all the parameters of RBF NN are updated in real time. The stability of this control law is rigorously proved by following the Lyapunov stability theory and shown by the experimental simulations. The fact that all of the weighting factors, width and center of RBF NN have been updated implies that this scheme utilizes all the possibilities in RBF NN to make the controller robust and precise while the mobile robot is following un-known trajectories. The performance of this new algorithm has been compared to the conventional RBF NN controller where some of the parameters are adjusted for robustness.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.528-536
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• 2020

As humanoid robot technology advances, the use of robots for performance is increasing. As a result, studies are being conducted to increase the scope of use of robots in performances by making them natural like humans. Among them, the use of motion capture technology is often used, and there are environmental inconveniences in preparing for motion capture, such as the need for IMU sensors or markers attached to each part of the body and precise high-performance cameras. In addition, for robots used in performance technology, there is a problem that they have to respond in real time depending on the unexpected situation or the audience's response. To make up for the above mentioned problems, in this paper, we proposed a real-time motion capture system by using a number of RGB-D cameras and creating natural robot motion similar to human motion by using motion-captured data.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.548-551
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• 1997

Performance of force tracking impedance control of robot manipulators is degraded by the uncertainties in the robot and environment dynamic model. The purpose of this paper is to improve the controller robustness by applying neural network. Neural networks are designed to learn the uncertainties in robot and environment model for compensating the uncertainties. The proposed scheme is verified through the simulation of 20DOF robot manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.77-83
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• 2003

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of revolute joint robot dynamics. The stability of the robot with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot system is stable, and has excellent trajectory tracking performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.435-438
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• 2002

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of serial link robot dynamics. The stability of the robot with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot system is stable, and has excellent trajectory tracking performance.