Seung-You Na

Implementation of Pipeline Monitoring System Using Bio-memetic Robots

We present a pipeline monitoring system based on bio-memetic robot in this paper. A bio-memetic robot exploring pipelines measures temperature, humidity, and vibration. The principal function of pipeline monitoring robot for the exploring pipelines is to recognize the shape of pipelines. We use infrared distance sensor to recognize the shape of pipelines and potentiometer to measure the angle of motor mounting infrared distance sensor. For the shape recognition of pipelines, the number of detected pipelines is used during only one scanning of distance. Three fuzzy classifiers are used for the number of detected pipelines, and the classifying results are presented in this paper.

Implementation of Underwater Entertainment Robots Based on Ubiquitous Sensor Networks

ABSTRACT We present an autonomous entertainment dolphin robot system based on ubiquitous sensor networks(USN). Generally, It is impossible to apply to USN and GPS in underwater bio-mimetic robots. But An Entertainment dolphin robot which presented in this paper operates on the water not underwater. Navigation of the underwater robot in a given area is based on GPS data and the acquired position information from deployed USN motes with emphasis on user interaction. Body structures, sensors and actuators, governing microcontroller boards, and swimming and interaction features are described for a typical entertainment dolphin robot. Actions of mouth-opening, tail splash or water blow through a spout hole are typical responses of interaction when touch sensors on the body detect users’ demand. Dolphin robots should turn towards people who demand to interact with them, while swimming autonomously. The functions that are relevant to human-robot interaction as well as robot movement such as path control, obstacle detection and avoidance are managed by microcontrollers on the robot for autonomy. Distance errors are calibrated periodically by the known position data of the deployed USN motes.Keywords:Entertainment Underwater Robot, Ubiquitous Sensor Networks, Bio-Memetics

Application of MAP and MLP Classifier on Raman Spectral Data for Classification of Liver Disease

In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.

USN based sonar localization system for a fish robot

Localization is the most important functions in mobile robots. There are so many approaches to realize this essential function in wheel based mobile robots, but it is not easy to find similar examples in small underwater robots. It is presented the sonar localization system using ubiquitous sensor network for a fish robot in this paper. A fish robot uses GPS and sonar system to find exact localization. Although GPS is essential tool to obtain positional information, this device doesn`t provide reasonable resolution in localization. To obtain more precise localization information, we use several Ubiquitous Sensor Networks (USN) motes with sonar system. Experimental results show that a fish robot obtains more detailed positional information.

Audio-Visual Localization and Tracking of Sound Sources Using Kalman Filter

With the high interest on robot technology and application, the research on artificial auditory systems for robot is very active. In this paper we discuss sound source localization and tracing based on audio-visual information. For video signals we use face detection based on skin color model. Also, binaural-based DOA is used as audio information. We integrate both informations using Kalman filter. The experimental results show that audio-visual person tracking Is useful, specially in the case that some informations are not observed.

Photo Sensor Based Measurement and Noise Reduction of Dynamic Weights

Due to various types of errors added to dynamic weight measurement data, proper methods to reduce measurement errors are required to produce reliable weights. It is very difficult to reduce the measurement error due to excessive oscillation of the system. To cope with parasitic types of errors in real systems, information provided by the photo sensors are utilized and combined in such a way to reduce the measurement errors of load cells. In addition to four channels of load cells from a model trailer, photo sensors are used to obtain the information to compensate the error induced from vertical movement of the vehicle due to the variation of ground level. A model trailer system is run to verify the effectiveness of the proposed method to reduce noise of dynamic weight measurements.