• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.45 no.2
• /
• pp.124-132
• /
• 2017

With the growth of interest in the UAVs, the study of the UAV collision avoidance is in progress. Lidar, Video camera, laser sensor, and ultrasonic sensor may be utilized for collision avoidance of UAV. In this paper, the characteristics of MB 1230 ultrasonic sensor is analyzed through the experiment. When concurrently using multitudinous ultrasonic sensors, ultrasonic sensors do not generate correct measurement values. To solve ultrasonic sensor interference, sequentially transmitting ultrasonics signal is suggested by using 'Enable' signal input of ultrasonic sensor, so by activating each ultrasonic sensor gradually. This proposed solution is also verified by experimentation.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2014.02a
• /
• pp.277.2-277.2
• /
• 2014

For next-generation electronic applications, human-machine interface devices have recently been demonstrated such as the wearable computer as well as the electronic skin (e-skin). For integration of those systems, it is essential to develop many kinds of components including displays, energy generators and sensors. In particular, flexible sensing devices to detect some stimuli like strain, pressure, light, temperature, gase and humidity have been investigated for last few decades. Among many condidates, a pressure sensing device based on organic field-effect transistors (OFETs) is one of interesting structure in flexible touch displays, bio-monitoring and e-skin because of their flexibility. In this study, we have investigated a flexible e-skin based on highly sensitive, pressure-responsive OFETs using microstructured ferroelectric gate dielectrics, which simulates both rapidly adapting (RA) and slowly adatping (SA) mechanoreceptors in human skin. In SA-type static pressure, furthermore, we also demonstrate that the FET array can detect thermal stimuli for thermoreception through decoupling of the input signals from simultaneously applied pressure. The microstructured highly crystalline poly(vinylidene fluoride-trifluoroethylene) possessing piezoelectric-pyroelectric properties in OFETs allowed monitoring RA- and SA-mode responses in dyanamic and static pressurizing conditions, which enables to apply the e-skin to bio-monitoring of human and robotics.

• Journal of Sensor Science and Technology
• /
• v.27 no.1
• /
• pp.13-20
• /
• 2018

Gas sensors based on metal oxide semiconductors are used in numerous applications including monitoring indoor air quality and detecting harmful substances like volatile organic compounds. Nanostructures, for example, nanoparticles, nanotubes, nanodomes, and nanofibers have been widely utilized to improve gas sensing properties of metal oxide semiconductors, and this increases the effective surface area, resulting in participation of more target gas molecules in the surface reaction. In the recent times, 1-dimensional (1D) metal oxide nanostructures fabricated using anodic oxidation have attracted great attention due to their high surface-to-volume ratio with large-area uniformity, reproducibility, and capability of synthesis under ambient air and pressure, leading to cost-effectiveness. Here, we provide a brief overview of 1D metal oxide nanostructures fabricated by anodic oxidation and their gas sensing properties. In addition, recent progress on thin film-based anodic oxidation for application in gas sensors is introduced.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.3
• /
• pp.411-419
• /
• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.6
• /
• pp.852-862
• /
• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.5
• /
• pp.425-433
• /
• 2020

Three-dimensional data has been used for different applications such as robotics, building reconstruction, and so on. 3D data can be generated from an optical camera or a laser scanner. Especially, a wearable multi-sensor system including the above-mentioned sensors is an optimized structure that can overcome the drawbacks of each sensor. After finding the geometric relationships between sensors, georeferencing of the datasets acquired from the moving system, should be carried out. Especially, in an indoor environment, error propagation always causes problem in the georeferencing process. To improve the accuracy of this process, other sources of data were used to combine with LiDAR (Light Detection and Ranging) data, and various registration methods were also tested to find the most suitable way. More specifically, this paper proposed a new process of NDT (Normal Distribution Transform) to register the LiDAR point cloud, with additional information from other sensors. For real experiment, a wearable mapping system was used to acquire datasets in an indoor environment. The results showed that applying the new process of NDT and combining LiDAR data with IMU (Inertial Measurement Unit) information achieved the best result with the RMSE 0.063 m.

• Journal of Sensor Science and Technology
• /
• v.13 no.1
• /
• pp.41-46
• /
• 2004

There is currently much interest in the development of instruments that emulate the senses of humans. Increasingly, there is demand for mimicking the human sense of smell, which is a sophisticated chemosensory system. An electronic nose system is applicable to a large area of industries including environmental monitoring. We have designed a protable electronic nose system using an array of commercial chemical gas sensors for recognizing and analyzing the various odours. In this paper, we have implemented a portable electronic nose system using an array of gas sensors for recognizing and analyzing VOCs (Volatile Organic Compounds) in the field. The accuracy of a portable electronic nose system may be lower than an instrument such as GC/MS (Gas Chromatography/Mass Spectrometer). However, a portable electronic nose system could be used on the field and showed fast response to pollutants in the field. Several different algorithms for odours recognition were used such as BP (Back-Propagation) or LM-BP (Levenberq-Marquardt Back-Propagation). We applied RBF (Radial Basis Function) Network for recognition and quantifying of odours, which has simpler and faster compared to the previously used algorithms such as BP and LM-BP.

• Journal of Information Processing Systems
• /
• v.17 no.6
• /
• pp.1179-1190
• /
• 2021

A data acquisition and monitoring system was developed for an automated system of a smart fish farm. The fish farm is located in Jang Hang, South Korea, and was designed as circulation filtration system. Information of every aquaculture pool was automatically measured by pH sensors, dissolved oxygen sensors, and water temperature sensors and the data were stored in the database in a remoted server. Modbus protocol was used for gathering the data which were further used to optimize the pool water quality to predict the rate of growth and death of fish, and to deliver food automatically as planned by the fish farmer. By using JSON protocol, the collected data was delivered to the user's PC and mobile phone for analysis and easy monitoring. The developed monitoring system allowed the fish farmers to improve fish productivity and maximize profits.

• Journal of Internet Computing and Services
• /
• v.23 no.2
• /
• pp.37-44
• /
• 2022

With the outbreak of COVID-19, non-face-to-face activities such as remote learning and telecommuting have increased rapidly. As a result, the number of people staying at home and the number of hours spent inside the house have also increased since the pandemic. Our team had previously worked on methods for detecting abnormal conditions in a person's health in various circumstances within the house by converging single sensor-based algorithms. In our previous research, we installed IoT sensors indoors to detect people emergency situations requiring aids, the scope of detection was limited to indoor space due to the limitation in sensors. In this study, we have come up with a system that integrates our previous study with a new method for detecting abnormal conditions in outdoor environments using outdoor security cameras and wearable devices. The proposed system enables users to be notified of emergency situations in both indoor and outdoor areas and respond to them as quickly as possible.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.293-298
• /
• 2023

The military is facing a continuous decrease in personnel, and in order to cope with potential accidents and challenges in operations, efforts are being made to reduce the direct involvement of personnel by utilizing the latest technologies. Recently, the use of various sensors related to Manned-Unmanned Teaming and artificial intelligence technologies has gained attention, emphasizing the need for flexible utilization methods. In this paper, we propose four dataset construction methods that can be used for effective training of robots that can be deployed in military operations, utilizing not only RGB image data but also data acquired from IR image sensors. Since there is no publicly available dataset that combines RGB and IR image data, we directly acquired the dataset within buildings. The input values were constructed by combining RGB and IR image sensor data, taking into account the field of view, resolution, and channel values of both sensors. We compared the proposed method with conventional RGB image data classification training using the same learning model. By employing the proposed image data fusion method, we observed improved stability in training loss and approximately 3% higher accuracy.