• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.53-58
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• 2016

Various jumping robot platforms have been developed to carry out missions such as rescues, explorations, or inspections of dangerous environments. We suggested a jumping robot platform using energy conversion of the elastic body like the bar of a pole vault, which is the main part in which elastic force occurs. The compliant link was optimized by an optimization method based on Taguchi methodology, and the robot's leaping ability was improved. Among the parameters, the length, width, and thickness of the link were selected as design variables first while the others were fixed. The level of the design variables was settled, and an orthogonal array about its combination was made. In the experiment, dynamic simulations were conducted using the DAFUL program, and response table and sensitivity analyses were performed. We found optimized values through a level average analysis and sensitivity analysis. As a result, the maximum leaping height of the optimized robot increased by more than 6.2% compared to the initial one, and these data will be used to design a new robot.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.110-119
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• 2010

This paper aims to add the autonomous driving capability to the inverted pendulum system which maintains the inverted pendulum upright stably. For the autonomous driving from the starting position to the goal position, the motion control algorithm is proposed based on the dynamics of the inverted pendulum robot. To derive the dynamic model of the inverted pendulum robot, a three dimensional robot coordinate is defined and the velocity jacobian is newly derived. With the analysis of the wheel rolling motion, the dynamics of inverted pendulum robot are derived and used for the motion control algorithm. To maintain the balance of the inverted pendulum, the autonomous driving strategy is derived step by step considering the acceleration, constant velocity and deceleration states simultaneously. The driving experiments of inverted pendulum robot are performed while maintaining the balance of the inverted pendulum. For reading the positions of the inverted pendulum and wheels, only the encoders are utilized to make the system cheap and reliable. Even though the derived dynamics works for the slanted surface, the experiments are carried out in the standardized flat ground using the inverted pendulum robot in this paper. The experimental data for the wheel rolling and inverted pendulum motions are demonstrated for the straight line motion from a start position to the goal position.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.363-372
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• 1997

In this paper, the design and the implementation of the adaptive learning rate neural network controller for an articulate robot, which is being developed (or) has been developed in our Automatic Control Laboratory, are mainly discussed. The controller reduces software computational load via distributed processing method using multiple CPU's, and simplifies hardware structures by the time-division control with TMS32OC31 DSP chip. Proposed neural network controller with adaptive learning rate structure using expert's heuristics can improve learning speed. The proposed controller verifies its superiority by comparing response characteristics of conventional controller with those of the proposed controller that are obtained from the experiments for the 5 axis vertical articulated robot. We, also, present the generalization property of proposed controller for unlearned trajectory and the change of load through experimental data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.808-811
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• 2009

Robovie-R2 [1], developed by ATR, is a 110cm high, 60kg weight, two wheel drive, human like robot. It has two arms with dynamic fingers. It also has a position sensitive detector sensor and two cameras as eyes on his head for recognizing his surrounding environment. Recent years, we have carried out a project to integrate new functions into Robovie-R2 so as to make it possible to be used in a dining room in healthcare center for helping serving meal for elderly. As a new function, we have developed software system for adaptive movement control of Robovie-R2 that is primary important since a robot that cannot autonomously control its movement would be a dangerous object to the people in dining room. We used the cameras on Robovie-R2's head to catch environment images, applied our original algorithm for recognizing obstacles such as furniture or people, so as to control Roboie-R2's movement. In this paper, we will focus our algorithm and its results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.569-579
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• 2013

Robot control and image processing using a smartphone and Wi-Fi communication is introduced. The robot has a wheel and quadruped mechanism that is transformed according to the environment and is mainly used for drug bottle delivery. The captured image on the camera is transmitted to the smartphone in the form of stream data, and the image data is processed in the smartphone to enable the robot to identify an object and to control the robot itself. A network was constructed so that only image data from the stream data was used, and an image processing scheme to identify the drug bottle and deliver it to a person using a robot arm is also presented. In this study, image processing techniques and algorithms were purely implemented on a smartphone with considerable computational power and multiple functions rather than a computer, which contributes to the intelligence and miniaturization of the robot system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.33-40
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• 2015

This paper presents the design and implementation of the educational remote controlled robot system including remote sensing in the embedded environment. The design of sensing information processing, software design and template design mechanism for the programming practice are introduced. LPC1769 using Cortex-M3 core as CPU, LPCXPRESSO as debugging environment, C language as firmware development language and FreeRTOS as OS are used in development environment. The control command is received via RF communication by the server and the robot system which is operated by driving the various sensors. The educational procedure is from robot demo operation program as hands-on practice and then compiling, loading of the basic robot operation program, already supplied. Thereafter the verification is checked by using the basic robot operation to allow demo operation such as hands-on-training procedure. The original protocol is designed via RF communication between server and robot system, and the satisfied performance result is presented by analyzing the robot sensing data processing.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.213-221
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• 2017

Utilizing the existing polishing robot prevents unrestricted change of direction, driving, and identification of driving pathway. To overcome this barrier, driving mechaism has been designed with Omniwheels with encoders and RSSI method of beacon system has been utilized to identify the driving path by position recognition. Due to the wheel characteristics, the Omniwheel mobile robot generates greater slip than the conventional mobile robot, which reduces its driving accuracy. Therefore, to improve the driving accuracy, the localization is conducted through the fusion of encoder and RSSI of beacon data to compensate for the errors caused by Dead Reckoning and inaccuracy of sensors. Finally, the localization accuracies of the proposed and conventional indoor localization method are compared to show effectiveness of the proposed driving control for a polishing robot.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.955-961
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• 2006

The global ultrasonic system for the self-localization of a mobile robot consists of several ultrasonic transmitters fixed at some reference positions in the global coordinates of robot environment. By activating the ultrasonic transmitters, the mobile robot is able to get the distance to the ultrasonic transmitters and compute its own position in the global coordinate. Due to the limitation on the ultrasonic signal strength and beam width as well as the environmental obstacles however, the ultrasonic signals from some generator may not be transmitted to the robot. Thus, instead of activating the all ultrasonic transmitters, it is necessary to select some ultrasonic generators to activate based on the current robot position. In this paper, we propose a selective activation algorithm for self-localization with the global ultrasonic system. The selective activation algorithm gets the meaningful ultrasonic data at every sampling instants, which results in the faster and more accurate response of the self-localization than the conventional sequential activation. Through the self-localization and path following control, we verify the effectiveness of the proposed selective activation algorithm.