• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.1
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• pp.47-56
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• 1999

As the density of logic gates of VLSI chips has rapidly increased, more number of I/O pins has been required. This results in bigger package size and higher packager cost. The package cost is higher than the cost of bare chips for high I/O count VLSI chips. As the density of logic gates increases, the reduction method of the number of I/O pins for a given complexity of logic gates is required. In this paper, we propose the novel I/O interface circuit using CTR (Constant-Transition-Rate) code to reduce 50% of the number of I/O pins. The rising and falling edges of the symbol pulse of CTR codes contain 2-bit digital data, respectively. Since each symbol of the proposed CTR codes contains 4-bit digital data, the symbol rate can be reduced by the factor of 2 compared with the conventional I/O interface circuit. Also, the simultaneous switching noise(SSN) can be reduced because the transition rate is constant and the transition point of the symbols is widely distributed. The channel encoder is implemented only logic circuits and the circuit of the channel decoder is designed using the over-sampling method. The proper operation of the designed I/O interface circuit was verified using. HSPICE simulation with 0.6 m CMOS SPICE parameters. The simulation results indicate that the data transmission rate of the proposed circuit using 0.6 m CMOS technology is more than 200 Mbps/pin. We implemented the proposed circuit using Altera's FPGA and confimed the operation with the data transfer rate of 22.5 Mbps/pin.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.438-444
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• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.102-110
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• 2004

In this paper, we propose a VLSI structure of real-time image compression and reconstruction processor using 2-D discrete wavelet transform and implement into a hardware which use minimal hardware resource using ASIC library. In the implemented hardware, Data path part consists of the DWT kernel for the wavelet transform and inverse transform, quantizer/dequantizer, the huffman encoder/huffman decoder, the adder/buffer for the inverse wavelet transform, and the interface modules for input/output. Control part consists of the programming register, the controller which decodes the instructions and generates the control signals, and the status register for indicating the internal state into the external of circuit. According to the programming condition, the designed circuit has the various selective output formats which are wavelet coefficient, quantization coefficient or index, and Huffman code in image compression mode, and Huffman decoding result, reconstructed quantization coefficient, and reconstructed wavelet coefficient in image reconstructed mode. The programming register has 16 stages and one instruction can be used for a horizontal(or vertical) filtering in a level. Since each register automatically operated in the right order, 4-level discrete wavelet transform can be executed by a programming. We synthesized the designed circuit with synthesis library of Hynix 0.35um CMOS fabrication using the synthesis tool, Synopsys and extracted the gate-level netlist. From the netlist, timing information was extracted using Vela tool. We executed the timing simulation with the extracted netlist and timing information using NC-Verilog tool. Also PNR and layout process was executed using Apollo tool. The Implemented hardware has about 50,000 gate sizes and stably operates in 80MHz clock frequency.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.4
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• pp.459-466
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• 2012

The accurate engine output is basically one of important factors for the analysis of engine performance. Nowadays in-cylinder pressure analysis in internal combustion engine is also an indispensable tool for engine research and development, environment regulation and maintenance of engine. Here, it is essential more than anything else to find the correct TDC(Top Dead Center) position for the accuracy of engine output for diesel engine. Therefore this study is to analyze affecting factors to TDC position in 2-stroke large low speed engine and to suggest new method for determining correct TDC position. In the previous paper, it was mentioned that the accuracy of engine output is influenced by the determination of exact TDC position, and that 'Angle based sampling' method is better than 'Time based sampling' method in terms of precision. It was confirmed that there is 'Loss of angle', which is a difference between compression pressure peak and real TDC caused by heat loss and blow by of gas leakage. Consequently we invented new method, called "An improved method of time based sampling", which can obtain the correct engine output. The results by this method with compensating loss of angle was shown the same result by the 'Angle based sampling' method in encoder setting cylinder. This study is to suggest the new measuring method of exact engine output, and to examnine the reliance on the outcome.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.368-375
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• 2013

Failure of small bore piping welds is a recurring problem at nuclear power plants. And the socket weld cracking in small bore piping has caused unplanned plant shutdowns for repair and high economic impact on the plants. Consequently, early crack detection, including the detection of manufacturing defects, is of the utmost importance. Until now, the surface inspection methods has been applied according to ASME Section XI requirements. But the ultrasonic inspection as a volumetric method is also applying to enforce the inspection requirement. However, the conventional manual ultrasonic inspection techniques are used to detect service induced fatigue cracks. And there was uncertainty on manual ultrasonic inspection because of limited access to the welds and difficulties with contact between the ultrasonic probe and the OD(outer diameter) surface of small bore piping. In this study, phased array ultrasonic inspection technique is applied to increase inspection speed and reliability. To achieve this object, the 3.5 MHz phased array ultrasonic transducer are designed and fabricated. The manually encoded scanner was also developed to enhance contact conditions and maintain constant signal quality. Additionally inspection system is configured and inspection procedure is developed.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.6
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• pp.447-458
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• 2003

A high speed multiplier is essential basic building block for digital signal processors today. Typically iterative algorithms in Signal processing applications are realized which need a large number of multiply, add and accumulate operations. This paper describes a macro block of a parallel structured multiplier which has adopted a 32$\times$32-b regularly structured tree (RST). To improve the speed of the tree part, modified partial product generation method has been devised at architecture level. This reduces the 4 levels of compression stage to 3 levels, and propagation delay in Wallace tree structure by utilizing 4-2 compressor as well. Furthermore, this enables tree part to be combined with four modular block to construct a CSA tree (carry save adder tree). Therefore, combined with four modular block to construct a CSA tree (carry save adder tree). Therefore, multiplier architecture can be regularly laid out with same modules composed of Booth selectors, compressors and Modified Partial Product Generators (MPPG). At the circuit level new Booth selector with less transistors and encoder are proposed. The reduction in the number of transistors in Booth selector has a greater impact on the total transistor count. The transistor count of designed selector is 9 using PTL(Pass Transistor Logic). This reduces the transistor count by 50% as compared with that of the conventional one. The designed multiplier in 0.25${\mu}{\textrm}{m}$ technology, 2.5V, 1-poly and 5-metal CMOS process is simulated by Hspice and Epic. Delay is 4.2㎱ and average power consumes 1.81㎽/MHz. This result is far better than conventional multiplier with equal or better than the best one published.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.703-710
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• 2016

In robotics research, accurate estimation of current robot position is important to achieve motion control of a robot. In this research, we focus on a sensor fusion method to provide improved position estimation for a wheeled mobile robot, considering two different sensor measurements. In this case, we fuse camera-based vision and encode-based odometry data using Kalman filter techniques to improve the position estimation of the robot. An external camera-based vision system provides global position coordinates (x, y) for the mobile robot in an indoor environment. An internal encoder-based odometry provides linear and angular velocities of the robot. We then use the position data estimated by the Kalman filter as inputs to the motion controller, which significantly improves performance of the motion controller. Finally, we experimentally verify the performance of the proposed sensor fused position estimation and motion controller using an actual mobile robot system. In our experiments, we also compare the Kalman filter-based sensor fused estimation with two different single sensor-based estimations (vision-based and odometry-based).

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.518-524
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• 2011

This paper presents a study on the calibration of accelerometer data in the gyroscope free inertial navigation system(GFINS) using fuzzy inference system(FIS). The conventional INS(inertial navigation system) which can measure yaw rate and linear velocity using inertial sensors as the gyroscope and accelerometer. However, the INS is difficult to design as small size and low power because it uses the gyroscope. To solve the problem, the GFINS which does not have the gyroscope have been studied actively. However, the GFINS has cumulative error problem still. Hence, this paper proposes Fuzzy-GFINS which can calibrate the data of an accelerometer using FIS consists of two inputs that are ratio between linear velocity of the autonomous ground vehicle(AGV) and the accelerometer and ratio between linear velocity of the encoders and the accelerometer. To evaluate the proposed Fuzzy-GFINS, we made the AGV with Mecanum wheels and applied the proposed Fuzzy-GFINS. In experimental result, we verified that the proposed method can calibrate effectively data of the accelerometer in the GFINS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.723-730
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• 2015

In this paper, a location tracking compensation algorithm based on the Least-Squares Method ($LCA_{LSM}$) was proposed to improve the autonomous tracking efficiency for the docent robot in exhibition hall, and the performance of the $LCA_{LSM}$ is analyzed by several practical experiments. The proposed $LCA_{LSM}$ compensates the collected location coordinates for the robot using the Least-Squares Method (LSM) in order to reduce the cumulated errors that occur in the Encoder/Giro sensor (E/G) and to enhance the measured tracking accuracy rates in the autonomous tracking of the robot in exhibition hall. By experiments, it was confirmed that the average error reduction rates of the $LCA_{LSM}$ are higher as 4.85% than that of the $LCA_{KF}$ in Scenario 1 (S1) and Scenario 2 (S2), respectively on the location tracking. In addition, it was also confirmed that the standard deviation in the measured errors of the $LCA_{LSM}$ are much more low and constant compared to that of the E/G sensor and the $LCA_{KF}$ in S1 and S2 respectively. Finally, we see that the suggested $LCA_{LSM}$ can execute more the stabilized location tracking than the E/G sensors and the $LCA_{KF}$ on the straight lines of S1 and S2 for the docent robot.