• 제목/요약/키워드: distance estimation

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Recurrent Neural Network Based Distance Estimation for Indoor Localization in UWB Systems (UWB 시스템에서 실내 측위를 위한 순환 신경망 기반 거리 추정)

  • Jung, Tae-Yun;Jeong, Eui-Rim
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.4
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    • pp.494-500
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    • 2020
  • This paper proposes a new distance estimation technique for indoor localization in ultra wideband (UWB) systems. The proposed technique is based on recurrent neural network (RNN), one of the deep learning methods. The RNN is known to be useful to deal with time series data, and since UWB signals can be seen as a time series data, RNN is employed in this paper. Specifically, the transmitted UWB signal passes through IEEE802.15.4a indoor channel model, and from the received signal, the RNN regressor is trained to estimate the distance from the transmitter to the receiver. To verify the performance of the trained RNN regressor, new received UWB signals are used and the conventional threshold based technique is also compared. For the performance measure, root mean square error (RMSE) is assessed. According to the computer simulation results, the proposed distance estimator is always much better than the conventional technique in all signal-to-noise ratios and distances between the transmitter and the receiver.

A Study on the Development of Height Estimation Sensor for Gondola-typed Façade Robot (곤돌라형 외벽 유지보수 로봇의 수직위치 센서 개발에 관한 연구)

  • Yoon, Jongsu;Kim, Dong Yeop;Park, Chang-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.4
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    • pp.383-389
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    • 2013
  • Demand for high-rising building has arisen. However, its maintenance is usually executed by labour. It could have a severe problem. We proposed a gondola robot to solve it. In this paper, we designed a height estimation sensor for this gondola. It is consist of pan-tilt unit, ARS sensor, and laser sensor. The pan-tilt unit keeps the laser sensor to indicate the gravity direction by referencing the ARS. The laser sensor's range is vertical distance from gondola to ground. However, if there is an obstacle under the gondola, the distance includes its height. To filter it out, we apply a Kalman filter for the height estimation. If the estimated height is changed extremely, the filter decides that there is an obstacle. Then, it remembers the height of obstacle. Other extreme changes of height estimations are reflected. The experimental results using the proposed sensor system show detail flow of the height estimation.

Shape Descriptor for 3D Foot Pose Estimation (3차원 발 자세 추정을 위한 새로운 형상 기술자)

  • Song, Ho-Geun;Kang, Ki-Hyun;Jung, Da-Woon;Yoon, Yong-In
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.2
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    • pp.469-478
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    • 2010
  • This paper proposes the effective shape descriptor for 3D foot pose estimation. To reduce processing time, silhouette-based foot image database is built and meta information which involves the 3D pose of the foot is appended to the database. And we proposed a modified Centroid Contour Distance whose size of the feature space is small and performance of pose estimation is better than the others. In order to analyze performance of the descriptor, we evaluate time and spatial complexity with retrieval accuracy, and then compare with the previous methods. Experimental results show that the proposed descriptor is more effective than the previous methods on feature extraction time and pose estimation accuracy.

Multi-Human Behavior Recognition Based on Improved Posture Estimation Model

  • Zhang, Ning;Park, Jin-Ho;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.24 no.5
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    • pp.659-666
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    • 2021
  • With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

Study on Modeling and Simulation for Fire Localization Using Bayesian Estimation (화원 위치 추정을 위한 베이시안 추정 기반의 모델링 및 시뮬레이션 연구)

  • Kim, Taewan;Kim, Soo Chan;Kim, Jong-Hwan
    • Journal of the Society of Naval Architects of Korea
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    • v.58 no.6
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    • pp.424-430
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    • 2021
  • Fire localization is a key mission that must be preceded for an autonomous fire suppression system. Although studies using a variety of sensors for the localization are actively being conducted, the fire localization is still unfinished due to the high cost and low performance. This paper presents the modeling and simulation of the fire localization estimation using Bayesian estimation to determine the probabilistic location of the fire. To minimize the risk of fire accidents as well as the time and cost of preparing and executing live fire tests, a 40m × 40m-virtual space is created, where two ultraviolet sensors are simulated to rotate horizontally to collect ultraviolet signals. In addition, Bayesian estimation is executed to compute the probability of the fire location by considering both sensor errors and uncertainty under fire environments. For the validation of the proposed method, sixteen fires were simulated in different locations and evaluated by calculating the difference in distance between simulated and estimated fire locations. As a result, the proposed method demonstrates reliable outputs, showing that the error distribution tendency widens as the radial distance between the sensor and the fire increases.

A Study on the Workability Estimation of Water-Soluble Rubberized Asphalt Waterproofing of Spray Type - Focus on the Material Condition - (수용성 뿜칠형 고무 아스팔트 방수재의 시공성 평가에 관한 연구 - 재료 조건을 중심으로 -)

  • Oh, Sang-Keun;Bae, Kee-Sun;Lee, Won-Hun;Kwak, Kyu-Sung;Choi, Eun-Su
    • Journal of the Korea Institute of Building Construction
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    • v.3 no.2
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    • pp.141-148
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    • 2003
  • This study deals with the estimation of material properties according to the construction condition for water-soluble rubberized asphalt waterproofing material of spray type. In this study, the waterproofing material property by the spray construction method is suggested by means of estimation its tensile performance and temperature dependency according to mix proportion ratio(4:1, 8:1), referenced viscosity and solid content (A:360cps, 76%, B:580cps, 79%, C:490cps, 70%), spray angle($30^{\circ}$, $45^{\circ}$, $60^{\circ}$), and spray distance(30cm, 50cm, 70cm). The result of testing are as follows. (1) The mix proportion ratio of principal agent and hardener is 4:1. (2) The viscosity referenced and solid content are 490cps and 70%. (3) The spray angle referenced is $45.^{\circ}$ (4) The distance referenced from concrete surface to spray gun is 40~50cm.

A Camera Pose Estimation Method for Rectangle Feature based Visual SLAM (사각형 특징 기반 Visual SLAM을 위한 자세 추정 방법)

  • Lee, Jae-Min;Kim, Gon-Woo
    • The Journal of Korea Robotics Society
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    • v.11 no.1
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    • pp.33-40
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    • 2016
  • In this paper, we propose a method for estimating the pose of the camera using a rectangle feature utilized for the visual SLAM. A warped rectangle feature as a quadrilateral in the image by the perspective transformation is reconstructed by the Coupled Line Camera algorithm. In order to fully reconstruct a rectangle in the real world coordinate, the distance between the features and the camera is needed. The distance in the real world coordinate can be measured by using a stereo camera. Using properties of the line camera, the physical size of the rectangle feature can be induced from the distance. The correspondence between the quadrilateral in the image and the rectangle in the real world coordinate can restore the relative pose between the camera and the feature through obtaining the homography. In order to evaluate the performance, we analyzed the result of proposed method with its reference pose in Gazebo robot simulator.

Modeling of the Safety Distance between Defrost Heater and Plastic Inner Wall of Refrigerator (제상 히터와 냉장고 플라스틱 내벽 사이의 안전거리에 대한 모델링)

  • Jung, Young;Shin, Jong-Min;Tikhonov, Alexei V.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.15 no.3
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    • pp.196-202
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    • 2003
  • Two dimensional modeling was carried out to find the safety distance between the defrost heater and the plastic inner wall of domestic refrigerator Estimation was processed for the three cases; the estimation of plastic wall temperature (1) without any protection, (2) with an aluminum foil attached on a wall, and (3) with an aluminum shield installed between heater and wall. The former two cases are found to be dangerous during defrosting process, because the temperatures of inner wall reach above 80'C , which is the upper temperature limit of the wall material. The case with an aluminum shield is considered to be safe by maintaining the temperature of the wall in the range of 6$0^{\circ}C$ during defrosting process.

A Study on In-Flight Alignment Using the Flight Distance of Vehicle (항체의 비행거리 정보를 이용한 운항 중 정렬 기법 연구)

  • Yu, Hae-Sung
    • Journal of the Korea Institute of Military Science and Technology
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    • v.8 no.3 s.22
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    • pp.5-10
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    • 2005
  • This paper presents the new in-flight alignment method using the flight distance of vehicle in order to improve the performance of the heading error estimation. In the proposed method, the Kalman filter having the difference between GPS and SDINS position as measurements is used for levelling of SDINS and heading error is estimated utilizing the flight distance information. It is shown in the simulation results that the in-flight method proposed in this paper has the high accuracy in heading error estimation and the heading error can be very quickly estimated at the high speed vehicle, compared with the existing method using the Kalman filter.

Adaptive Kernel Estimation for Learning Algorithms based on Euclidean Distance between Error Distributions (오차분포 유클리드 거리 기반 학습법의 커널 사이즈 적응)

  • Kim, Namyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.561-566
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    • 2021
  • The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.