• 제목/요약/키워드: Multi-Sensor Model

검색결과 301건 처리시간 0.024초

An Adaptive Goal-Based Model for Autonomous Multi-Robot Using HARMS and NuSMV

  • Kim, Yongho;Jung, Jin-Woo;Gallagher, John C.;Matson, Eric T.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권2호
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    • pp.95-103
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    • 2016
  • In a dynamic environment autonomous robots often encounter unexpected situations that the robots have to deal with in order to continue proceeding their mission. We propose an adaptive goal-based model that allows cyber-physical systems (CPS) to update their environmental model and helps them analyze for attainment of their goals from current state using the updated environmental model and its capabilities. Information exchange approach utilizes Human-Agent-Robot-Machine-Sensor (HARMS) model to exchange messages between CPS. Model validation method uses NuSMV, which is one of Model Checking tools, to check whether the system can continue its mission toward the goal in the given environment. We explain a practical set up of the model in a situation in which homogeneous robots that has the same capability work in the same environment.

Utility Bounds of Joint Congestion and Medium Access Control for CSMA based Wireless Networks

  • Wang, Tao;Yao, Zheng;Zhang, Baoxian;Li, Cheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권1호
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    • pp.193-214
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    • 2017
  • In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

성층화 열용량 모델을 이용한 VAV 시스템 급기 제어 시뮬레이션 (Simulation of Supply Air Control in a VAV System Using a Stratified Lumped Thermal Model)

  • 문정우;김서영;김원년;조형희
    • 설비공학논문집
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    • 제12권7호
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    • pp.632-641
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    • 2000
  • The present study concerns the simulation of supply-air control in a variable air volume (VAV) system. A stratified lumped thermal model (multi-zone model) is suggested to predict local thermal response of an air-conditioned space. The effects of various thermal parameters such as the cooling system capacity, the thermal mass of air-conditioned space, the time delay of thermal effect, and the building envelope heat transmission are investigated in detail. Further, the influence of control parameters, PI control factor and the sensor location on a VAV system is quantitatively delineated. The results obtained show that the previous homogeneous lumped thermal model (1-zone model) may predict a significantly different thermal response in the air-conditioned space according to the sensor location.

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Multi-Sensor Signal based Situation Recognition with Bayesian Networks

  • Kim, Jin-Pyung;Jang, Gyu-Jin;Jung, Jae-Young;Kim, Moon-Hyun
    • Journal of Electrical Engineering and Technology
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    • 제9권3호
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    • pp.1051-1059
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    • 2014
  • In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

하지 외골격 로봇을 위한 인솔 센서시스템 및 보행 판단 알고리즘 개발 (Development of Insole Sensor System and Gait Phase Detection Algorithm for Lower Extremity Exoskeleton)

  • 임동환;김완수;미안 아쉬팍 알리;한창수
    • 한국정밀공학회지
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    • 제32권12호
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    • pp.1065-1072
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    • 2015
  • This paper is about the development of an insole sensor system that can determine the model of an exoskeleton robot for lower limb that is a multi-degree of freedom system. First, the study analyzed the kinematic model of an exoskeleton robot for the lower limb that changes according to the gait phase detection of a human. Based on the ground reaction force (GRF), which is generated when walking, to proceed with insole sensor development, the sensing type, location, and the number of sensors were selected. The center of pressure (COP) of the human foot was understood first, prior to the development of algorithm. Using the COP, an algorithm was developed that is capable of detecting the gait phase with small number of sensors. An experiment at 3 km/h speed was conducted on the developed sensor system to evaluate the developed insole sensor system and the gait phase detection algorithm.

CCAJS: A Novel Connect Coverage Algorithm Based on Joint Sensing Model for Wireless Sensor Networks

  • Sun, Zeyu;Yun, Yali;Song, Houbing;Wang, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권10호
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    • pp.5014-5034
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    • 2016
  • This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

Geo-referenced 영상 획득을 위한 휴대용 멀티센서 시스템 구축 및 정확도 평가 (Development of a Portable Multi-sensor System for Geo-referenced Images and its Accuracy Evaluation)

  • 이지훈;최경아;이임평
    • 한국측량학회지
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    • 제28권6호
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    • pp.637-643
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    • 2010
  • 본 연구에서는 비디오카메라와 GPS/MEMS IMU, UMPC를 결합하여 영상과 위치/자세 데이터를 획득하는 휴대용 멀티센서 시스템을 구축하였다. 구축된 시스템을 통해 획득된 데이터를 이용하여 지상기준점을 이용하지 않고 광속조정법 기반의 영상 geo-referencing을 수행하고 정확도 검증을 통해 시스템의 효용성을 평가하였다. 정확도 검증 결과, 지상점의 상대좌표 정확도는 RMSE가수 cm내외로 상당히 정확함을 확인할 수 있었다. 구축된 시스템은 대상 객체의 3차원 모델과 상대좌표를 획득하는데 있어서 충분히 활용 가능하다고 판단된다. 향후에는 시스템 및 카메라의 엄밀한 보정을 통해 절대좌표의 정확도를 개선할 예정이다.

무선센서 네트워크를 통한 실내 거주자의 일상생활 행동 모형 정립 연구 (A Study on Establishing Resident's Behavioral Model in Daily Living based on a Wireless Sensor Network)

  • 조승호
    • 한국컴퓨터정보학회논문지
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    • 제14권2호
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    • pp.129-138
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    • 2009
  • 고령화 사회를 넘어 고령사회를 눈앞에 두고 있는 우리나라에서 노인 문제는 더욱 심각할 것으로 예상되고 있다. 본 연구에서는 집 또는 복지/요양 시설에서 생활하고 있는 거주자들의 일상생활 행동 모형을 정립하는 연구를 수행하였다. 이를 위해 본 연구에서는 사건 발생을 중심으로 하는 일상 행동 모형 $W_{ip}(n)$을 제안하였다. 본 연구에서는 제안된 행동 모형을 기반으로 조도/온도 센서로 구성된 무선 센서 네트워크 시스템을 구축하였다. 본 연구에서 구축한 시스템에서 거주자들의 일상 행동 양상에 대하여 실험을 수행하였다. 실험을 통해서 거주자의 일상생활이 정규적인 범위에 있는지 벗어나 있는지 구분하고자 시도하였다. 제안된 일상 행동 모형이 미래에 집이나 사회복지 시설의 거주자들을 효과적으로 보살피는데 매우 잘 적용될 것임을 실험 결과들이 알려주고 있다.

다차량 추종 적응순항제어 (Multi-Vehicle Tracking Adaptive Cruise Control)

  • 문일기;이경수
    • 대한기계학회논문집A
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    • 제29권1호
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    • pp.139-144
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    • 2005
  • A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

다중연결 해양부유체의 모형시험 구조응답 예측정확도 향상을 위한 유전알고리즘을 이용한 센서배치 최적화 (Optimal Sensor Placement for Improved Prediction Accuracy of Structural Responses in Model Test of Multi-Linked Floating Offshore Systems Using Genetic Algorithms)

  • 심기찬;이강수
    • 한국전산구조공학회논문집
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    • 제37권3호
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    • pp.163-171
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    • 2024
  • 본 논문에서는 다목적 구조물인 다중연결 해양부유체를 대상으로 변형 기반 모드 차수축소법을 적용하고 차수축소모델의 구조응답 예측 성능을 향상시키기 위해 유전 알고리즘 기반의 센서 배치 최적화를 수행하였다. 다중연결 해양부유체의 차수축소모델 생성에 필요한 변형 기반 모드 데이터를 얻기 위해 다양한 규칙파랑하중조건에 대한 유체-구조 연성 수치해석을 수행하고 변형 기반 모드의 직교성, 자기상관계수를 이용하여 주요 변형 기반 모드를 선정하였다. 다중연결 해양부유체의 경우 차수축소모델의 구조응답 예측 성능이 계측 및 예측 구조응답 위치에 따라 민감하기 때문에 유전 알고리즘 기반의 최적화를 수행하여 최적의 센서 배치를 도출하였다. 최적화 결과, 모든 센서 배치 조합에 대한 차수축소모델 생성 및 예측 성능 평가 대비 약 8배의 계산 비용을 절감하였으며, 예측 성능 평가 지표인 평균 제곱근 오차가 초기 센서 배치보다 84% 감소하였다. 또한, 다중연결 해양부유체 모형시험 결과를 이용하여 불규칙파랑하중에 대한 최적화된 센서 배치의 차수축소모델의 구조응답 예측 성능을 평가 및 검증하였다.