• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.385-389
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• 2007

본 논문에서는 재난 구조 로봇의 목적을 수행하기 위한 Situation-aware Middleware 에 대해서 설명한다. 재난 구조 로봇은 정확한 정황인지와 빠른 정보 처리 능력이 필요하다. 하지만 실시간으로 수집되는 센서의 정보들은 재난 구조 로봇과 같은 인명 구조나 재해 수습을 위한 특정 목적을 수행하기 위해 설계된 지능형 로봇은 센서 정보의 시간과 무분별한 정보는 선별하여 수집해야 긴급 상황에서 효율적으로 대처 할 수 있다. 따라서 이 논문에서는 Q-MAR(QoS-Mission-Action-Resource)모델을 참조 하여, 특정 목적에 맞는 정황 정보들을 선별 수집 융합 하는 새로운 Goal-driven Situation-Aware Middleware(GDSAM)를 제안하여 이 문제를 해결 하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.440-442
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• 2019

메카넘 휠과 4족 및 6족의 다리를 갖는 탐사 및 재난 로봇을 바탕으로 휠과 6족이 함께 존재하는 탐사 및 재난 로봇이다. 평지나 완만한 길에선 메카넘 휠을 이용해 빠르게 굴러가는 모습을 볼 수 있다. 그리고 계단이나 산악지대 같은 경사가 높고 휠로 이동하기 힘든 공간은 부착된 6족 다리를 이용해 걸어 나가는 모습을 볼 수 있다. 이러한 휠과 6족이 결합된 탐사 및 재난 로봇은 사람의 조종 없이 영상처리와 여려가지 센서를 이용해 스스로 자율주행 하는 모습을 볼 수 있다.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.220-229
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• 2018

In the midst of disaster, such as an earthquake or a nuclear radiation exposure area, there are huge risks to send human crews. Many robotic researchers have studied to send UGVs in order to replace human crews at dangerous environments. So far, two-dimensional camera information has been widely used for teleoperation of UGVs. Recently, three-dimensional information based teleoperations are attempted to compensate the limitations of camera information based teleoperation. In this paper, the 3D map information of indoor and outdoor environments reconstructed in real-time is utilized in the UGV teleoperation. Further, we apply the LTE communication technology to endure the stability of the teleoperation even under the deteriorate environment. The proposed teleoperation system is performed at explosive disposal missions and their feasibilities could be verified through completion of that missions using the UGV with the Explosive Ordnance Disposal (EOD) team of Busan Port Security Corporation.

• Fire Science and Engineering
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• v.27 no.6
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• pp.83-88
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• 2013

Catastrophic disasters are sprouting out recently, i.e., the radiation leaks and the hydrofluoric acid gas leaks, etc. The restoration work for these kinds of disasters is very harmful and dangerous for human beings to handle themselves, thus allowing manless robots to fly the reconnaissance planes over to the disaster stricken areas and do the necessary work instead. For this endeavor and purpose, we created and tested an intelligent robot that can inspect those areas, using Mbed (ARM processor) technology temperature sensors and gas sensors aided by CAM (Computer-Aided Manufacturing) cameras. Also, HTTP Server, PC, androids and their combined efforts allow their remote controlled operation from far away with timing control. These intelligent robots can be on duty for 24 hours, minimizing the accidents and crimes and what not, and can respond more quickly when these misfortunes actually happen. We can anticipate the economic effects as well, derived from the reduced needs for hiring human resources.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.337-340
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• 2005

Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.909-915
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• 2008

Recently, the interests in the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration, and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with an autonomous travelling function to cope with unexpected terrains and obstacles. This means that they should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents a method for extracting terrain information, that is, slope and roughness from elevation maps as a prior step of traversability analysis. Slope is extracted using the curve fitting based on the least squares method and roughness using three metrics and their weighted average. The effectiveness of the proposed method is verified on both a fractal map and the world model map of a real terrain.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.233-236
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• 2008

Recently, the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with autonomous travelling function to cope with unexpected terrains and obstacles. This means that unmanned robots should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents an algorithm for extracting terrain information from elevation maps as an early step of traversability analysis. Slope and roughness information are extracted from a world terrain map based on least squares method and fractal theory, respectively. The effectiveness of the proposed algorithm is verified on both fractal and real terrain maps.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.85-94
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• 2020

AI-based smart factory technologies are only increase short-term productivity. To solve this problem, collaborative intelligence combines human teamwork, creativity, AI speed, and accuracy to actively compensate for each other's shortcomings. However, current automation equipmens require high safety measures due to the high disaster intensity in the event of an accident. In this paper, we design and implement a factory safety control system that uses a depth camera to implement workers and facilities in the virtual world and to determine the safety of workers through simulation.