• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of Sasang Constitutional Medicine
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• v.18 no.1
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• pp.118-131
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• 2006

1. Objective Pulse diagnosis is generally applied to Traditional Oriental Medicine but not to Sasang Constitution diagnosis. Recently new pulse analyzer using array piezoresistive sensor and multi-channel robot arm developed. It reflects Oriental Medical Doctors' diagnostic processes, and its reproducibility test was done at Korea Institute of Oriental Medicine. We performed this study to set parameters diagnosing Sasang Constitution. 2. Methods One hundred thirty three subjects participated in this study. They are healty and approved this study. Before being tested with pulse analyzer, they had interview with Sasang Constitution Specialist to diagnose their Sasang Constitution. We established some useful parameters from parameters of pulse analyzer according to the Original Texts of Oriental Medicine and clinical experiences to analyze with clinical data of this study. 3. Results (I) There is a significant difference in pre-dicrotic notch time among all parameters of pulse analyzer in Sasang Constitution groups(P=0.047). (2) There is a significant difference in maximum pulse pressure in 33 to 48 year Sasang Constitution groups(P=0.010). (3) There is a significant difference in frequency width in 17 to 32 year Sasang Constitution groups(P=0.002). (4) There is a significant difference in CFS value in groups which OMD diagnoses; Floating & Sinking pulse(P=0.020). (5) There is a significant difference in pulse rate in groups which OMD diagnoses; Rapid & Slow pulse(P=0.000). (6) There is a significant difference in maximum pulse pressure in groups which OMD diagnoses; Deficient & Solid pulse(P=0.000). 4. Conclusions Analyzing parameters in each Sasang Constitution group, we found it shows significant difference in maximum pulse pressure and corresponding tendency in coefficient of floating & sinking pulse with theories of Sasang Consti-tutional Medicine. As we accumulate more clinical data, we will establish algorithm to diagnose Sasang Constitution using a pulse analyzer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.147-155
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• 2015

In this paper, we consider a mobile sensor network for monitoring a polluted area where human beings cannot access. Due to the limited sensing range of individual unmanned vehicles, they need to cooperate to achieve an effective sensing coverage and move to a more polluted region. In order to address the limitations of sensing and communication ranges, we propose a hazardous substance monitoring network based on virtual force algorithms, and develop a testbed. In the considered monitoring network, each unmanned vehicle achieves an optimal coverage and move to the highest interest area based on neighboring nodes sensing values and locations. By using experiments based on the developed testbed, we show that the proposed monitoring network can autonomously move toward a more polluted area and obtain a high weighted coverage.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.29-34
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• 2015

Brain-computer interface (BCI) is being studied for convenient life in various application fields. The purpose of this study is to investigate a changing electroencephalography (EEG) for precise motion of a robot or an artificial arm. Three subjects who participated in this experiment performed three-task: Grip, Move, Relax. Acquired EEG data was extracted feature data using two feature extraction algorithm (power spectrum analysis and multi-common spatial pattern). Support vector machine (SVM) were applied the extracted feature data for classification. The classification accuracy was the highest at Grip class of two subjects. The results of this research are expected to be useful for patients required prosthetic limb using EEG.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.194-201
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• 2004

Optical fibers are indispensable fer optical communication systems that transmit large volumes of data at high speed. But the aligning technology under the sub-micron accuracy is required for the precise axis adjustment and connection. For the purpose of precise alignment of the optical arrays, in this research, we have developed the 12-axis(with 8 automated axis and 4 manual axis) automatic optical fiber alignment system including the image processing-based searching system, the automatic loading system using the robot and the suction toot and the automatic UV bonding system. In order to obtain the sub-micron alignment accuracy, two 4-axis PC-based motion controllers and the two 50nm resolution 6-aixs micro-stage actuated by micro stepping motors are adopted. The fiber aligning procedure consists of two steps. Firstly, the optical wave guide and an input optical array are aligned by the 6-axis input micro-stage with the IR camera. The image processing technique is introduced to reduce primary manual aligning time and result in achieving the 50% decrease of aligning time. Secondly, the IR camera is replaced by the output micro-stage and a wave guide and two optical arrays are aligned simultaneously before the laser power intensity delivered to the optical powermeter reached the threshold value. When the aligning procedure is finished, the wave guide and arrays are W bonded. The automatic loading/unloading system is also introduced and the entire wave guide handing time is reduced significantly compared to the former commercial aligning system.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.132-143
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• 2017

While working in an industrial environment which requires extended periods of upright posture; workers tend to develop muscle fatigue due to the constant load on lower-limb muscles. In addition, when working while bending knees; muscle fatigue of lower back and hamstrings is increased due to the abnormal posture. This can lead to damage of muscles, induce musculoskeletal disorders, and reduce long-term working efficiency. Recent medical studies have shown that long-term working in an upright posture can induce musculoskeletal disorders such as foot fatigue, edema, pain and varicose veins. Likewise, medical and rehabilitation expenses have grown due to the increase in musculoskeletal conditions suffered by workers. For this problem, we aim to develop a device that can reduce the physical fatigue on the lower limbs by supporting the weight of workers during the extended periods of upright and bending postures in the industrial environments. In this paper, we have designed and manufactured a wearable weight support system; with a user intention algorithm that the users can maintain various postures. For validation of the developed system, we measured the muscle activity of the users wearing the system with EMG sensors.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.102-113
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• 2014

This paper suggests a novel hardware architecture of a real-time rectification which is to remove vertical parallax of an image occurred in the pre-processing stage of stereo matching. As an off-line step, Matlab Toolbox which was designed by J.Y Bouguet, was used to calculate calibration parameter of the image. Then, based on the Heikkila and Silven's algorithm, rectification hardware was designed. At this point, to enhance the precision of the rectified image, floating-point unit was generated by using Xilinx Core Generator. And, we confirmed that proposed hardware design had higher precision compared to other designs while having the ability to do rectification in real-time.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.506-512
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modifY rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verifY the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.