• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.602-608
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• 2011

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs $x_i$, i=1~6, the hidden layer consists of two hidden units for hidden outputs $o_j$, j=1~2, and the output layer consists of two units for the outputs ${\tau}_k$, k=1~2. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels. The initial q value was set to [0, 5, ${\pi}$].

• Journal of IKEEE
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• v.25 no.1
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• pp.148-155
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• 2021

As robot technology advances, research on the driving system of mobile robots is actively being conducted. The driving system of a mobile robot configured based on two-wheels and four-wheels has an advantage in unidirectional driving such as a straight line, but has disadvantages in turning direction and rotating in place. A ball robot using a ball as a wheel has an advantage in omnidirectional movement, but due to its structurally unstable characteristics, balancing control to maintain attitude and driving control for movement are required. By estimating the position from an encoder attached to the motor, conventional ball robots have a limitation, which causes the accumulation of errors during driving control. In this study, a driving control system was proposed that estimates the position coordinates of a ball robot through image processing and uses it for driving control. A driving control system including an image processing unit, a communication unit, a display unit, and a control unit for estimating the position of the ball robot was designed and manufactured. Through the driving control experiment applying the driving control system of the ball robot, it was confirmed that the ball robot was controlled within the error range of ±50.3mm in the x-axis direction and ±53.9mm in the y-axis direction without accumulating errors.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1092-1098
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• 2007

A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1676-1681
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• 2003

The attachment of mobile vehicle is necessary for the automated operation on the inclined or vertical walls of steel structures. Since the vehicle requires attaching devices additionally, its overall efficiency can be reduced by the devices. Therefore, external shapes of mobile vehicles have to be researched to give the effective movement on the vertical face. For the design of mobile vehicle, the guideline has been derived from the modeling of wall-climbing, so that the vehicle should have a specific external shape for vertical movement due to the gravitational force. Hence, some adequate arrangement of attaching device to the mobile vehicle has been presented for the effective movement. In the experiments with four permanent magnetic wheels, a plausible result was achieved as a vertical attaching force of 185.2(N), a friction force of 153.8(N) and a curvature radius of 1.4m. The mobile vehicle should be modified according to the proposed design guideline. and then it could be applied to a specific operation as an appropriate external shape. Also, Further research is recommended on an optimal posture and a moving method in a specific application. as the attaching force ortho vehicle can be affected by its posture.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.129-136
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• 2010

In this paper proposed the sensor fusion algorithm between a gyroscope and an accelerometer to maintain the inverted posture with two wheels which can make the robot body move to the desired destination. Mobile inverted robot fall down to the forward or reverse direction to converge to the stable point. Therefore, precise information of tilt angles and quick posture control by using the information are necessary to maintain the inverted posture, hence this paper proposed the sensor fusion algorithm between a gyroscope to obtain the angular velocity and a accelerometer to compensate for the gyroscope. Kalman Filter is normally used for the algorithm and numerous research is progressing at the moment. However, a high-performing DSP and systems are needed for the algorithm. This paper realized the robot control method which is much simpler but able to get desired performance by using the sensor fusion algorithm and PID control.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.266-271
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• 2015

This paper presents the driving and bouncing control of a robotic vehicle for entertainment and transportation. The robotic vehicle is aimed to carry two passengers with a balancing mechanism by two wheels. To maximize the entertaining purpose, not only the balancing control performance but the bouncing control performance is implemented. Passengers can select different driving modes such as regular driving mode, balancing mode, and bouncing mode. Experimental studies of the balancing control performance as well as the bouncing control performance are conducted to see the feasibility as an entertainment robotic vehicle.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.4
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• pp.85-92
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• 2020

Applications for the unmanned aerial vehicle (UAV) have expanded enormously in recent years. Of all its various technologies, the UAV's ability to take off and land in a moving environment is particularly required for military or oceanic usage. In this study, we develop a novel leveling platform that allows the UAV to stably take off and land even on uneven terrains or in moving environments. The leveling platform is composed of an upper pad and a lower mobile base. The upper pad, from which the UAV can take off or land, is designed in the form of a 2 degrees of freedom (DOF) gimbal mechanism that generates the leveling function. The lower mobile base has a four-wheel drive structure that can be operated remotely. We evaluate the developed leveling platform by performing extensive experiments on both the horizontal terrain and the 5-degree ramped terrain, and confirm that the leveling platform successfully maintains the horizontal pose on both terrains. This allows the UAV to stably take off and land in moving environments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.