• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.304-309
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• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.231-236
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• 2019

Background/Objectives: This paper proposes a dual mode feedback-controlled cycling system for children with spastic cerebral palsy to rehabilitate upper extremities. Repetitive upper limb exercise in this therapy aims to both reduce and analyze the abnormal torque patterns of arm movements in three- dimensional space. Methods/Statistical analysis: We designed an exercycle robot which consists of a BLDC motor, a torque sensor, a bevel gear and bearings. Mechanical structures are customized for children of age between 7~13 years old and induces reaching and pulling task in a symmetric circulation. The shafts and external frames were designed and printed using 3D printer. While the child performs active/passive exercise, angular position, angular velocity, and relative torque of the pedal shaft are measured and displayed in real time. Findings: Experiment was designed to observe the features of a cerebral palsy child's exercise. Two children with bilateral spastic cerebral palsy participated in the experiment and conducted an active exercise at normal speed for 3 sets, 15 seconds for each. As the pedal reached 90 degrees and 270 degrees, the subject showed minimum torque, in which the child showed difficulty in the pulling task of the cycle. The passive exercise assisted the child to maintain a relatively constant torque while visually observing the movement patterns. Using two types of exercise enabled the child to overcome the abnormal torque measured in the active data by performing the passive exercise. Thus, this system has advantage not only in allowing the child to perform the difficult task, which may contribute in improving the muscle strength and endurance and reducing the spasticity but also provide customizable system according to the child's motion characteristic. Improvements/Applications: Further study is needed to observe how passive exercise influences the movement characteristics of an active motion and how customized experiment settings can optimize the effect of pediatric rehabilitation for spastic cerebral palsy.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1022-1027
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• 2003

The Motion controllers provide the sophisticated performance and enhanced capabilities we can see in the movements of robotic systems. Several types of motion controllers are available, some based on the kind of overall control system in use. PLC (Programmable Logic Controller)-based motion controllers still predominate. The many peoples use MCU (Micro Controller Unit)-based board level motion controllers and will continue to in the near-term future. These motion controllers control a variety motor system like robotic systems. Generally, They consist of large and complex circuits. PLC-based motion controller consists of high performance PLC, development tool, and application specific software. It can be cause to generate several problems that are large size and space, much cabling, and additional high coasts. MCU-based motion controller consists of memories like ROM and RAM, I/O interface ports, and decoder in order to operate MCU. Additionally, it needs DPRAM to communicate with host PC, counter to get position information of motor by using encoder signal, additional circuits to control servo, and application specific software to generate a various velocity profiles. It can be causes to generate several problems that are overall system complexity, large size and space, much cabling, large power consumption and additional high costs. Also, it needs much times to calculate velocity profile because of generating by software method and don't generate various velocity profiles like arbitrary velocity profile. Therefore, It is hard to generate expected various velocity profiles. And further, to embed real-time OS (Operating System) is considered for more reliable motion control. In this paper, the structure of chip-based precision motion controller is proposed to solve above-mentioned problems of control systems. This proposed motion controller is designed with a FPGA (Field Programmable Gate Arrays) by using the VHDL (Very high speed integrated circuit Hardware Description Language) and Handel-C that is program language for deign hardware. This motion controller consists of Velocity Profile Generator (VPG) part to generate expected various velocity profiles, PCI Interface part to communicate with host PC, Feedback Counter part to get position information by using encoder signal, Clock Generator to generate expected various clock signal, Controller part to control position of motor with generated velocity profile and position information, and Data Converter part to convert and transmit compatible data to D/A converter.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.39-47
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• 2019

We propose a method to improve the performance of spontaneous speech recognizers by extending their phone set using speech data. In the proposed method, we first extract variable-length phoneme-level segments from broadcast speech signals, and convert them to fixed-length latent vectors using an long short-term memory (LSTM) classifier. We then cluster acoustically similar latent vectors and build a new phone set by choosing the number of clusters with the lowest Davies-Bouldin index. We also update the lexicon of the speech recognizer by choosing the pronunciation sequence of each word with the highest conditional probability. In order to analyze the acoustic characteristics of the new phone set, we visualize its spectral patterns and segment duration. Through speech recognition experiments using a larger training data set than our own previous work, we confirm that the new phone set yields better performance than the conventional phoneme-based and grapheme-based units in both spontaneous speech recognition and read speech recognition.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.155-161
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• 2019

Electroencephalography (EEG), a representative method of identifying temporal and spatial changes in brain activity, is a voluntary electrical activity measurable in the human scalp. Various interface technologies have been provided to control EEG activity, and it is possible to operate a machine such as a wheelchair or a robot through brainwaves. The characteristics of EEG data are collected in various types of channels in real time, and a server system for analyzing them is required to have an independent and lightweight system for the platform. In these days, the Spring platform is used as a large business server as an independent, lightweight server system. In this paper, we propose an EEG analysis system using the Spring server system. Using the proposed system, the reliability of EEG control can be enhanced, and analysis and control interface expansion can be provided in various aspects such as game and medical areas.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.854-856
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• 2014

Has been released of make it possible to control the using for smart devices of a wide variety home appliances and electronics in smart appliances in accordance with the one person multi devices. In addition, is increasing rapidly for the number of the product on cleaning robot and refrigerator, air conditioning, TV, etc. these devices are using the implement up DLNA system. And at home and abroad for development and has provided with Iot and Alljoyn such systems. But currently using home appliances or electronic devices of there are a lot of the operating system non installed than the installed products. In addition, smart appliances do not use for user than buying existing electronic products a lot more. In addition, more occur for smart appliances of that do not use for the user on smart appliances rather than buying existing electronics. In this paper, Suggested and implemented for system of control such as smart devices to existed home appliance on not have an operating system, Using mobile device for want users to quantify the data to transfer from arduino board.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.89-96
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• 2009

As increasing the number of digital control devices installed on aircrafts and their transmission speed, various digital data buses have been introduced to provide reliable and high-speed characteristics. These characteristics of avionics data bus are highly related on the fault-tolerant performance which can make minimize jitter and loss during data transfer. In this paper, we concerned about a new traffic shaping scheme for increasing the reliability of Avionics Full Duplex Switched Ethernet (AFDX) systems based on ARINC 664 standard. We note that the conventional AFDX with a single regulator per virtual link system may produce aggregated traffics as the number of virtual links increasing. The aggregated traffic results in large jitters among frames. To remedy for the jitter and loss of data, we propose a dual regulator scheme for the AFDX system. The purpose of the additional regulator is to additionally regulate aggregated traffics from a number of per virtual link regulators. Using NS-2 simulator, we show that the proposed scheme provides a better performance than the single regulator one. It is worthwhile note that the proposed AFDX with Dual Regulator scheme can be employed to not only aircraft networks but other QoS sensitive networks for robot and industrial control systems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.663-668
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• 2003

This paper presents a new observation system which is useful to observe the scene of the remote controlled robot vision. This system is composed of a motionless camera and head motion detector with a motion sensor. The motionless camera has a fish eye lens and is for observing a hemisphere space. The head motion detector has a motion sensor is for defining an arbitrary subspace of the hemisphere space from fish eye lens. Thus processing the angular information from the motion sensor appropriately, the direction of face is estimated. However, since the fisheye image is distorted, it is unclear image. The partial domain of a fish eye image is selected by head motion, and this is converted to perspective image. However, since this conversion enlarges the original image spatially and is based on discrete data, crevice is generated in the converted image. To solve this problem, interpolation based on an intensity of the image is performed for the crevice in the converted image (space problem). This paper provides the experimental results of the proposed observation system with the head motion detector and perspective image conversion using the proposed conversion and interpolation methods, and the adequacy and improving point of the proposed techniques are discussed.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.