• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.241-250
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• 2023

This paper describes the posture stabilization control of a bipedal transformer robot being developed for military use. An inverted pendulum model with a rectangular that considers the robot's inertia is proposed, and a posture stabilization moment that can maintain the body tilt angle is derived by applying disturbance observer and state feedback control. In addition, vertical force and posture stabilization moments that can maintain the body height and balance are derived through QP optimization to obtain the necessary torques and vertical force for each foot. The roll and pitch angles of the IMU sensor attached to the robot's feet are reflected in the ankle joint to enable flexible adaptation to changes in ground inclination. Finally, the effectiveness of the proposed algorithm in posture stabilization is verified by comparing and analyzing the difference in body tilt angle due to disturbances and ground inclination changes with and without algorithm application, using Gazebo dynamic simulation and a down-scale test platform.

• ETRI Journal
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• v.44 no.1
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• pp.135-146
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• 2022

The importance of big data analytics has become apparent with the increasing volume of data on the Internet. The amount of data will increase even more with the widespread use of Internet of Things (IoT). One of the most important application areas of the IoT is healthcare. This study introduces new real-time data analytics architecture for an IoT-based smart healthcare system, which consists of a wireless sensor network and a radio-frequency identification technology in a vertical domain. The proposed platform also includes high-performance data analytics tools, such as Kafka, Spark, MongoDB, and NodeJS, in a horizontal domain. To investigate the performance of the system developed, a diagnosis of Wolff-Parkinson-White syndrome by logistic regression is discussed. The results show that the proposed IoT data analytics system can successfully process health data in real-time with an accuracy rate of 95% and it can handle large volumes of data. The developed system also communicates with a riverbed modeler using Transmission Control Protocol (TCP) to model any IoT-enabling technology. Therefore, the proposed architecture can be used as a time-saving experimental environment for any IoT-based system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.71-72
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• 2020

본 논문에서는 시간과 공간의 제약없이 작물의 생육환경을 관측하고 자동 및 원격으로 제어할 수 있는 스마트팜 플랫폼을 설계 및 구현하였다. 스마트팜 플랫폼은 환경 데이터 수집을 위한 다양한 아두이노 센서 모듈, 웹과 데이터베이스 서버, 애플리케이션을 이용한 자동 및 원격 제어, 총 3가지 기술로 구성된다. 사용자가 앱을 통하여 언제 어디에서나 농장 주변의 환경 정보를 조회하고 원격으로 제어하면 농사에 대한 노동력 절감 뿐만 아니라 시간적·공간적 구속으로부터 자유로워져 여유시간도 늘고 삶의 질도 개선될 수 있을 것으로 기대된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.321-322
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• 2022

Recently, in the field of health care, health management topics are being dealt with a lot. In particular, services are concentrated in the field of exercise, and many exercise equipment fused with the 4th industry-based technology are also appearing. In general, a form of collecting user's exercise information by mounting various sensors on exercise equipment and linking services based on this is representative. In this paper, we propose an efficient data transmission based on the design in the process of transmitting the exercise data generated by the equipment to the smartphone through the Bluetooth-based IoT sensor and transmitting it back to the exercise information analysis platform.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.221-228
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• 2024

As the importance of cardiovascular health is highlighted, research on its correlation with blood pressure, the most important indicator, is being actively conducted. Therefore, extensive clinical data is essential, but the measurement of the central arterial blood pressure waveform must be performed invasively within the artery, so the quantity and quality are limited. This study suggested a mock circulatory robot and artificial aorta to reproduce the blood pressure waveform generated by the overlap of forward and reflected waves. The artificial aorta was fabricated with biomimetic silicone to mimic the physiological structure and vascular stiffness of the human. A pressurizing chamber was implemented to prevent distortion of the blood pressure waveform due to the strain-softening of biomimetic silicone. The reproduced central arterial blood pressure waveforms have similar magnitude, shape, and propagation characteristics to humans. In addition, changes in blood pressure waveform due to aging were also reproduced by replacing an artificial aorta with various stiffness. It can be expanded to construct a biosignal database and health sensor testing platform, a core technology for cardiovascular health-related research.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• Spatial Information Research
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• v.19 no.4
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• pp.21-31
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• 2011

As large scaled natural or man-made disasters being increased, the demand for rapid responses for such emergent situations also has been ever-increasing. These responses need to acquire spatial information of each individual site rapidly for more effective management of the situations. Therefore, we are developing a close-range real-time aerial monitoring system based on a low altitude unmanned helicopter. This system can acquire airborne sensory data in real-time and generate rapidly geospatial information. The system consists of two main parts: aerial and ground parts. The aerial part includes an aerial platform equipped with multi-sensor(cameras, a laser scanner, a GPS receiver, an IMU) and sensor supporting modules. The ground part includes a ground vehicle, a receiving system to receive sensory data in real-time and a processing system to generate the geospatial information rapidly. Development and testing of the individual modules and subsystems have been almost completed. Integration of the modules and subsystems is now in progress. In this paper, we w ill introduce our system, explain intermediate results, and discuss expected outcome.

• Progress in Medical Physics
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• v.24 no.1
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• pp.61-67
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• 2013

In this study, we developed and evaluated the patient respiration training method which can help to avoid the problems for the limitation of RGRT applicable patient cases. By using the MEMS (micro-electro-mechanical-system) acceleration sensor, we measured movement of motion phantom. We had compared the response of MEMS with commercially introduced real time patient monitoring (RPM) system. We measured the response of the MEMS with 1 dimensional motion phantom movement for 2.5, 3.0, 3.5 second of period and the 2.0, 3.0, 4.0 cm of the amplitudes. The measured period error of the MEMS system was 0.6~6.0% compared with measured period using RPM system. We found that the shape of MEMS signals were similar with RPM system. From this study, we found the possibility of MEMS as patient training system.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.86-96
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• 2022

The development trend of jet fighter's avionics system architecture is the digitization of subsystem component functions, increased RF sensor sharing, fiber optic channel networks, and modularized integrated structures. The avionics system architecture of the fifth generation jet fighters (F-22, F-35) has evolved into an integrated modular avionics system based on computing function integration and RF integrated sensor systems. The integrated modular avionics system of jet fighters should provide improved combat power, fault tolerance, and ease of jet fighter control. To this aim, this paper presents the direction and requirements of the next-generation jet fighter's avionics system architecture through analysis of the fifth generation jet fighter's avionics system architecture. The core challenge of the integrated modularized avionic system architecture requirements for next-generation fighters is to build a platform that integrates major components and sensors into aircraft. In other words, the architecture of the next-generation fighters is standardization of systems, sensor integration of each subsystem through open interfaces, integration of functional elements, network integration, and integration of pilots and fighters to improve their ability to respond and control.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.249-261
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• 2020

Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.