• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.75-80
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• 2021

Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.120-128
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• 2012

The loop closure problem is one of the most challenging issues in the vision-based simultaneous localization and mapping community. It requires the robot to recognize a previously visited place from current camera measurements. While the loop closure often relies on visual bag-of-words based on point features in the previous works, however, in this paper we propose a line-based method to solve the loop closure in the corridor environments. We used both the floor line and the anchored vanishing point as the loop closing feature, and a two-step loop closure algorithm was devised to detect a known place and perform the global pose correction. We propose an anchored vanishing point as a novel loop closure feature, as it includes position information and represents the vanishing points in bi-direction. In our system, the accumulated heading error is reduced using an observation of a previously registered anchored vanishing points firstly, and the observation of known floor lines allows for further pose correction. Experimental results show that our method is very efficient in a structured indoor environment as a suitable loop closure solution.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.981-984
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• 2010

최근 유비쿼터스 사회로 진화해 가면서 위치정보의 중요성이 높아짐에 따라 실외를 대상으로 하는 서비스 뿐 아니라 실내를 중심으로 하는 위치기반서비스에 관심이 집중되고 있다. 실내에서 사용자나 사물의 위치를 정확히 파악하기 위한 기술이 요구됨에 따라 다양한 측정수단과 방식으로 연구가 진행되고 있다. 특히, 실내에 설치된 AP를 활용하는 것이 가능하여 무선 랜 환경을 이용한 연구가 주로 진행되고 있지만, 기존의 연구는 주로 정해진 환경이나 전용AP를 활용하고 있어 위치측정 장소의 변경 등 환경적 요인이 변경되면 시스템을 재구축해야 하는 경우가 발생하고, 기존의 AP를 활용하기에는 많은 어려움이 존재한다. 따라서 본 논문에서는 특정한 위치측정 장소에 의존하지 않고 이미 실내에 설치된 AP를 활용하기 위한 방안을 제시하여 사용자의 위치를 효과적으로 측정하고 모니터링하기 위한 실내위치측정시스템의 구축절차, 고려해야할 사항 및 위치측정방법에 관하여 연구를 진행한다. 본 연구결과를 활용할 경우, 무선 랜 환경을 효과적으로 활용한 실내위치측정시스템의 구축이 용이할 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.775-778
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• 2007

로봇의 응용과 활용분야는 현 산업의 주요 이슈가 되고 있다. 현재 싱글로봇의 효율적인 운영을 넘어 넓은 공간에서 중복적인 공간 탐색을 최소화하기 위한 멀티 로봇 운영 기법은 중요한 연구 주제 중에 하나로 부각되고 있다. 멀티 로봇을 효율적으로 운영하기 위해서는 멀티 로봇 시스템의 각 싱글 로봇의 움직임을 파악하여 효율적으로 업무를 할당 할 수 있는 관리체계가 필요하다. 멀티 로봇의 업무 할당과 중복 탐색 최소화를 위해 본 논문에서는 중앙 서버와 RFID 시스템을 이용한 청소 멀티 로봇 운영 기법을 제안한다. 제안한 시스템은 로봇의 localization, navigation 및 mapping을 효율적으로 수행하기 위해 RFID를 활용하고 최적의 청소 공간 할당을 위하여 중앙 서버가 멀티 로봇을 효율적으로 관리한다. 청소 멀티 로봇 시스템에서는 싱글 로봇과 비교하여 효율적인 로봇의 운영을 보장할 뿐만 아니라 각 싱글 로봇의 상태와 주변 상태를 고려한 fault-tolerance를 제공함으로써 로봇 운영의 신뢰성을 보장할 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.5
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• pp.488-495
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• 2012

The real-time indoor location technology using radio waves has been studied in a variety of environments. One of them, a ship which consists of steel structure has high reception rate but causes significant ranging error due to the reflection of radio waves. In order to reduce location measurement errors that occurs in such a environment, this paper, based on CSS of IEEE 802.15.4a, presents compensation algorithm for localization using modified bilateration and pyroelectric sensor in a ship. The proposed system reduces the number of fixed nodes by estimating the appropriate reception distance between mobile node and fixed node through the analysis of CSS characteristic in a narrow passage such as ship corridors. Also, in the corner section which the ranging errors are significantly fluctuated due to the reflection and diffraction of radio waves, we recognize the location by tracking the a moving section using modified bilateration technique and pyroelectric sensor. The experimental results show that the location accuracy and efficiency of the proposed algorithm are improved 86.2 % compared to general method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.73-82
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• 2010

Door is an important object to understand given environment and it could be used to distinguish with corridors and rooms. Doors are widely used natural landmark in mobile robotics for localization and navigation. However, almost algorithm for door recognition with camera is difficult real-time application because feature extraction and matching have heavy computation complexity. This paper proposes a method to recognize a door in corridor. First, we extract distinguished lines which have high possibility to comprise of door using Hough transformation. Then, we detect candidate of door region by applying previously extracted lines to first-stage visual fuzzy system. Finally, door regions are determined by verifying knob region in candidate of door region suing second-stage visual fuzzy system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.89-95
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• 2015

In this paper, we propose a real-time two-dimensional bar code detection system even at long range using a vision technique. We first perform short-range detection, and then long-range detection if the short-range detection is not successful. First, edge map generation, image binarization, and connect component labeling (CCL) are performed in order to select a region of interest (ROI). After interpolating the selected ROI using bilinear interpolation, a location symbol pattern is detected as the same as for short-range detection. Finally, the symbol pattern is arranged by applying inverse perspective transformation to localize bar codes. Experimental results demonstrate that the proposed system successfully detects bar codes at two or three times longer distance than existing ones even at indoor environment.