• Title/Summary/Keyword: fusion of sensor information

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Autonomous Mobile Robot Using Sensor Fusion (센서융합을 이용한 이동로봇의 자율주행)

  • Shin, Seonwoong;Oh, Seyeop;Yoo, Dongsang;Moon, Hyeonjoon;Kim, Sanghoon
    • Annual Conference of KIPS
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    • 2013.05a
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    • pp.867-868
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    • 2013
  • 본 논문은 물류창고와 같은 실내 공간에서 RFID와 초음파 센서등을 이용하여 이동로봇이 자율적으로 자신의 위치를 파악하고 관리자가 지정한 목표 물체를 인식하여 간단한 업무를 보조할 수 있는 기법을 제안한다. 실내공간엔 RFID를 지면과 목표물체에 설치하고 로봇은 RFID의 리더기와 물체 접근시 활용이 가능한 추가적 센서를 갖춤으로써 이동시 자기 위치를 실시간으로 파악하고 물체로부터도 고유정보를 얻는다. 초음파 센서 신호의 귀환시간을 활용하여 근접한 물체와의 상대 거리를 추출하고 바닥의 RFID로부터 이미 획득한 자기 위치를 조합하여 목표 물체의 절대 위치를 구한다. 이는 이동 로봇을 중심으로 한 경로지도를 실시간으로 작성하며 동시에 실내의 이동 가능 구조 및 목표 물체의 파악이 가능하여 이동로봇의 자율적 탐색을 위한 최적 경로 계획 수립에 활용 가능하다.

An Innovative Approach to Track Moving Object based on RFID and Laser Ranging Information

  • Liang, Gaoli;Liu, Ran;Fu, Yulu;Zhang, Hua;Wang, Heng;Rehman, Shafiq ur;Guo, Mingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.1
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    • pp.131-147
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    • 2020
  • RFID (Radio Frequency Identification) identifies a specific object by radio signals. As the tag provides a unique ID for the purpose of identification, RFID technology effectively solves the ambiguity and occlusion problem that challenges the laser or camera-based approach. This paper proposes an approach to track a moving object based on the integration of RFID and laser ranging information using a particle filter. To be precise, we split laser scan points into different clusters which contain the potential moving objects and calculate the radial velocity of each cluster. The velocity information is compared with the radial velocity estimated from RFID phase difference. In order to achieve the positioning of the moving object, we select a number of K best matching clusters to update the weights of the particle filter. To further improve the positioning accuracy, we incorporate RFID signal strength information into the particle filter using a pre-trained sensor model. The proposed approach is tested on a SCITOS service robot under different types of tags and various human velocities. The results show that fusion of signal strength and laser ranging information has significantly increased the positioning accuracy when compared to radial velocity matching-based or signal strength-based approaches. The proposed approach provides a solution for human machine interaction and object tracking, which has potential applications in many fields for example supermarkets, libraries, shopping malls, and exhibitions.

Low Rate VLC Receiver Design Using NCP302 Voltage Detector for IoT/IoL Connected Smart Homes

  • Lee, Beomhee;Mariappan, Vinayagam;Khudaybergenov, Timur;Han, Jungdo;Cha, Jaesang
    • International journal of advanced smart convergence
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    • v.7 no.4
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    • pp.50-56
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    • 2018
  • The Internet of Things (IoT) and Visible Light Communication (VLC) is opening up new services in lighting industry by integrating sensory network features in addition to standard illumination functionality. In this progressive developments, the next generation lighting devices for smart homes are capable to sense the environmental conditions and transfer the captured data through lights to gateway controller to access remotely. The smart home environmental sensor information's are few kbps only so VLC systems need to built-in with low rate light connectivity to transfer data to the gateway. To provide error free communication, the quality of a received light signal is important to be considered when designing an VLC receiver. Therefore, this paper proposes the design of robust low rate IoL receiver design using NCP302 voltage detector for micro controller to adapt the IoT/IoL front end module for system integration. To evaluate the proposed system performance, the Arduino UNO based IoT/IoL controller designed with lighting, sensors and lights connectivity interfaces. The experimental result shows that the robust interference rejection is feasible on proposed VOL receiver and possible to have an error-free communication up to 10 kbps at a low SNR using OOK modulation.

Finite Element Model Updating Based on Data Fusion of Acceleration and Angular Velocity (가속도 및 각속도 데이터 융합 기반 유한요소모델 개선)

  • Kim, Hyun-Jun;Cho, Soo-Jin;Sim, Sung-Han
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.19 no.2
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    • pp.60-67
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    • 2015
  • The finite element (FE) model updating is a commonly used approach in civil engineering, enabling damage detection, design verification, and load capacity identification. In the FE model updating, acceleration responses are generally employed to determine modal properties of a structure, which are subsequently used to update the initial FE model. While the acceleration-based model updating has been successful in finding better approximations of the physical systems including material and sectional properties, the boundary conditions have been considered yet to be difficult to accurately estimate as the acceleration responses only correspond to translational degree-of-freedoms (DOF). Recent advancement in the sensor technology has enabled low-cost, high-precision gyroscopes that can be adopted in the FE model updating to provide angular information of a structure. This study proposes a FE model updating strategy based on data fusion of acceleration and angular velocity. The usage of both acceleration and angular velocity gives richer information than the sole use of acceleration, allowing the enhanced performance particularly in determining the boundary conditions. A numerical simulation on a simply supported beam is presented to demonstrate the proposed FE model updating approach.

Contrast Enhancement Based on Weight Mapping Retinex Algorithm (Contrast 향상을 위한 가중치 맵 기반의 Retinex 알고리즘)

  • Lee, Sang-Won;Song, Chang-Young;Cho, Seong-Soo;Kim, Seong-Ihl;Lee, Won-Seok;Kang, June-Gill
    • 전자공학회논문지 IE
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    • v.46 no.4
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    • pp.31-41
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    • 2009
  • The Image sensor of digital still camera has a limited dynamic range. In high dynamic range scenes, a picture often turns out to be underexposed or overexposed. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, it happens the unbalanced contrast enhancement which is the global contrast increased, and the local contrast decreased in the high dynamic range scenes. In this paper, to enhance the both global and local contrast, we propose the weight mapping retinex algorithm. Weight map is composed of the edge and exposure data which are extracted in the each retinex image, and merged with the retinex images in the fusion processing. According to the output picture comparing and numerical analysis, the proposed algorithm gives the better output image with the increased global and local contrast.

Adjustment of Exterior Orientation Parameters Geometric Registration of Aerial Images and LIDAR Data (항공영상과 라이다데이터의 기하학적 정합을 위한 외부표정요소의 조정)

  • Hong, Ju-Seok;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.5
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    • pp.585-597
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    • 2009
  • This research aims to develop a registration method to remove the geometric inconsistency between aerial images and LIDAR data acquired from an airborne multi-sensor system. The proposed method mainly includes registration primitives extraction, correspondence establishment, and EOP(Exterior Orientation Parameters) adjustment. As the registration primitives, we extracts planar patches and intersection edges from the LIDAR data and object points and linking edges from the aerial images. The extracted primitives are then categorized into horizontal and vertical ones; and their correspondences are established. These correspondent pairs are incorporated as stochastic constraints into the bundle block adjustment, which finally precisely adjusts the exterior orientation parameters of the images. According to the experimental results from the application of the proposed method to real data, we found that the attitude parameters of EOPs were meaningfully adjusted and the geometric inconsistency of the primitives used for the adjustment is reduced from 2 m to 2 cm before and after the registration. Hence, the results of this research can contribute to data fusion for the high quality 3D spatial information.

Development of Gas Type Identification Deep-learning Model through Multimodal Method (멀티모달 방식을 통한 가스 종류 인식 딥러닝 모델 개발)

  • Seo Hee Ahn;Gyeong Yeong Kim;Dong Ju Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.12
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    • pp.525-534
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    • 2023
  • Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

A Study on Colored LED Tag Recognition Method based on 8MP CMOS Sensor (8MP CMOS센서기반 Colored LED Tag 인식 기법에 대한 연구)

  • Lee, Min-Woo;Jeong, Sun-Ho;Yang, Seung-Youn;Shin, Jae-Kwon;Kim, Jin-Tae;Lee, Jung-Hoon;Cha, Jae-Sang
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.1435-1435
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    • 2015
  • 광고 및 홍보의 마케팅 수단의 일환으로써 점포별로 QR코드를 사용하는 사례가 급격히 늘고 있다. 정보도트의 일종인 QR코드의 경우는 스마트폰과 더불어 홍보수단의 일환으로 활용되는 사례가 증가하고 있는 반면 QR코드는 정보를 표현할 수 있는 디자인의 범위가 좁고, 전송할 수 있는 Data의 용량이 적으며, 어두운 환경에서의 인식률이 저하되는 단점이 있다. 이에 기존의 QR코드 보다 다양한 디자인이 가능하고 대용량의 Data 전송이 가능한 컬러코드가 대두되고 있다. 컬러코드란 4가지 색상(빨강, 파랑, 초록, 검정)을 이용한 매트릭스 형태의 코드로 각종 디지털 정보를 저장하는 새로운 개념의 데이터 표현 기술이며, 이는 각 컬러에 디지털 정보를 매핑(mapping)하여 콘텐츠나 URL 등의 실제 정보들을 제공하는 역할을 하도록 설계되어 있다. 8MP CMOS센서기반 Colored LED Patch 인식 기법은 VLC에 포함되는 하나의 기술로서 차세대 조명 및 정보 디스플레이 장치로 각광을 받고 있는 반도체 조명 기술인 광원 정보 인식 기법이다. 따라서, 본 논문에서는 8MP CMOS센서 기반 컬러코드 LED Patch 인식 기법에 대해 제안하였다. 8MP CMOS 센서를 이용한 Colored LED Patch 인식 기법 중 하나로서 위치 정보 서비스 등 다양한 정보 획득이 가능하도록 연구하였으며, 동영상, 웹사이트 링크 등 여러 형식에 적용이 가능하도록 하였다. 본 연구에서 사용되는 8MP CMOS센서를 기반 Colored LED Patch 인식 기법을 통해 컬러코드는 코드 플랫폼으로 연결되어 콘텐츠의 위치를 파악하고 이용자에게 콘텐츠 및 정보가 전송된다. 이는 QR코드보다 높은 인식률로 빠르고 편리하게 정보를 제공할 수 있었다. 본 논문에서는 상기 제안 기술을 통하여 LED Patch의 높은 주목성과 가시성을 확보하여 보다 효과적인 광고 및 홍보의 시인성을 확보할 수 있다. 향후 본 제안기술을 통하여 사회 안전망을 위한 위치 및 정보 서비스 제공이 가능하며, 효과적인 광고 효과를 도출할 수 있을 것으로 사료된다.

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Comparison of Multi-Static Sonar Target Positioning Performance (다중상태 소나망 위치 추정 성능 비교)

  • Park, Chee-Hyun;Ko, Han-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.4
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    • pp.166-172
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    • 2007
  • In this paper, we address the target positioning performance of Multi-Static sonar with respect to target positioning method and measurement error. Based on the analysis on two candidate solution approaches, namely, Least Square (LS) using range and angular information simultaneously and Maximum Likelihood (ML) using only range information as the existing information fusion methods for possible application to Multi-Static sonar, we propose to employ ML using range and angular information. Assuming that each sensor can receive range and angular information, we conduct representative comparison experiments over the existing and proposed methods under various measurement noise scenarios. We also investigate the target positioning performance according to number of sensors, distance between transmitter and receiver. According to the experimental results, RMSE of the proposed ML with distance and direction information is found to be more superior to ML using distance alone and to LS in case distance between transmitter and receiver is longer and number of receiver is smaller.

Feature Matching using Variable Circular Template for Multi-resolution Image Registration (다중 해상도 영상 등록을 위한 가변 원형 템플릿을 이용한 특징 정합)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1351-1367
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    • 2018
  • Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.