• Title/Summary/Keyword: Trajectory model

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Assessment of Long-Range Transport of Atmospheric Pollutants using a Trajectory Model with the puff Concept (퍼프 유적선모델에 의한 대기오염물질의 장거리수송량의 평가)

  • 정관영
    • Journal of Korean Society for Atmospheric Environment
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    • v.12 no.2
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    • pp.167-177
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    • 1996
  • To investigate the source-receptor relationships aerosol model has been used to simulate the distribution behavior of the yellow sand. Data for meteorological fields were obtained by Meso-scale Analysis and Prediction Model System/Seoul National University (MAPMS/SNU) for five days (10-14 April 1988). To obtain the distributions of concentration of yellow sand,the aerosol model has been modified to allow quantifications of relative concentration distributions of yellow sand. Source regions of yellow sand were delineated by soil maps of China and emission rate as a function of wind stress(Westphal et al., 1987). Using 3-dimensional wind fields the backward trajectories from 3 receptor grids at the layer of .sigma. =0.95, 0.9, 0.85, 0.8 were calculated. In order to facilitate quantitative assessment of source-receptor relationships, it was assumed that the perturbations in along-trajectory and cross-trajectory proceed linearly with time, in accord with Gaussian distribution characteristics. On the basis of this assumption, the probability fields were calculated from every grid point with source strength 1. Using these probability fields and emission retes, the potential contributions of upstream sources along the trajectories were estimated. The results of this study indicate that the application of trajectory modeling is useful in investigating the quantitative relationship between source and receptor regions.

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A Solution to Privacy Preservation in Publishing Human Trajectories

  • Li, Xianming;Sun, Guangzhong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.8
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    • pp.3328-3349
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    • 2020
  • With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users' privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users' behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users' privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary's background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users' privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.

Development of an Efficient Force Reflection Algorithm for a Virtual Environment (가상환경을 위한 효율적인 힘방향 알고리즘의 개발)

  • 권혁조;김기호;오재윤
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.60-63
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    • 2000
  • In this study, efficient force reflection algorithm is developed for the Haptic Display by using a proxy concept and friction model. When there are not any contacted obstacles the proxy is following human operator's command trajectory in the 3D virtual space. But when the operator's command trajectory is locating inside of the object, the proxy is constrained by the surface of the object. Here only with the information of the proxy position and operator's command trajectory at every time step, we can calculate the reflection force and its orientation. To display the friction force between two virtual stiff material which are sliding against each other, modified Karnopp's friction model is used. In the friction model, a damping term and a Stribeck effect term are included to display the relative velocity effect and stick-slip effect at the very low relative velocity region respectively.

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Base Station Placement for Wireless Sensor Network Positioning System via Lexicographical Stratified Programming

  • Yan, Jun;Yu, Kegen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.11
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    • pp.4453-4468
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    • 2015
  • This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

Time-Delay Control for the Implementation of the Optimal Walking Trajectory of Humanoid Robot

  • Ahn, Doo Sung
    • Journal of Drive and Control
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    • v.15 no.3
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    • pp.1-7
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    • 2018
  • Humanoid robots have fascinated many researchers since they appeared decades ago. For the requirement of both accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Humanoid robots are highly nonlinear, coupled, complex systems, accordingly the calculation of robot model is difficult and even impossible if precise model of the humanoid robots are unknown. Therefore, it is difficult to control using traditional model-based techniques. To realize model-free torque control, time-delay control (TDC) for humanoid robot was proposed with time-delay estimation technique. Using optimal walking trajectory obtained by particle swarm optimization, TDC with proposed scheme is implemented on whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the proposed TDC for humanoid robots.

Tourist Transition Model among Tourist Attractions based on GPS Trajectory

  • Kasahara, Hidekazu;Watabe, Takeshi;Iiyama, Masaaki
    • Journal of Smart Tourism
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    • v.1 no.2
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    • pp.19-25
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    • 2021
  • Before COVID-19, tourist destinations have experienced problems with congestion of both famous tourist attractions and public transportation. Over-tourism is not an issue at this time, but it is likely to rekindle after the COVID-19 pandemic ends. One method of mitigating over-tourism is to estimate tourist behavior using a tourist transition model and consequently adjust public transportation operations. In this study, we propose a construction method for a model of tourist transitions among tourist attractions based on tourist GPS trajectory data. We construct tourist transition models using actual trajectory data for tourists staying in the vicinity of Kyoto City. The results verify the model performance.

Construction and verification of nonparameterized ship motion model based on deep neural network

  • Wang Zongkai;Im Nam-kyun
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.170-171
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    • 2022
  • A ship's maneuvering motion model is important in a computer simulation, especially under the trend of intelligent navigation. This model is usually constructed by the hydrodynamic parameters of the ship which are generated by the principles of hydrodynamics. Ship's motion model is a nonlinear function. By using this function, ships' motion elements can be calculated, then the ship's trajectory can be predicted. Deeping neural networks can construct any linear or non-linear equation theoretically if there have enough and sufficient training data. This study constructs some kinds of deep Networks and trains this network by real ship motion data, and chooses the best one of the networks, uses real data to train it, then uses it to predict the ship's trajectory, getting some conclusions and experiences.

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A Study on ZMP Improvement of Biped Walking Robot Using Neural Network and Tilting (신경회로망과 틸팅을 이용한 이족 보행로봇의 ZMP 개선 연구)

  • Kim, Byoung-Soo;Nam, Kyu-Min;Lee, Soon-Geul
    • The Journal of Korea Robotics Society
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    • v.6 no.4
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    • pp.301-307
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    • 2011
  • Based on the stability criteria of ZMP (Zero Moment Point), this paper proposes an adjusting algorithm that modifies walking trajectory of a bipedal robot for stable walking by analyzing ZMP trajectory of it. In order to maintain walking balance of the bipedal robot, ZMP should be located within a supporting polygon that is determined by the foot supporting area with stability margin. Initially tilting imposed to the trajectory of the upper body is proposed to transfer ZMP of the given walking trajectory into the stable region for the minimum stability. A neural network method is also proposed for the stable walking trajectory of the biped robot. It uses backpropagation learning with angles and angular velocities of all joints with tilting to get the improved walking trajectory. By applying the optimized walking trajectory that is obtained with the neural network model, the ZMP trajectory of the bipedal robot is certainly located within a stable area of the supporting polygon. Experimental results show that the optimally learned trajectory with neural network gives more stability even though the tilting of the pelvic joint has a great role for walking stability.

A Capturing Algorithm of Moving Object using Single Curvature Trajectory (단일곡률궤적을 이용한 이동물체의 포획 알고리즘)

  • Choi Byoung-Suk;Lee Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.145-153
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    • 2006
  • An optimal capturing trajectory for a moving object is proposed in this paper based on the observation that a single-curvature path is more accurate than double-or triple-curvature paths. Moving distance, moving time, and trajectory error are major factors considered in deciding an optimal path for capturing the moving object. That is, the moving time and distance are minimized while the trajectory error is maintained as small as possible. The three major factors are compared for the single and the double curvature trajectories to show superiority of the single curvature trajectory. Based upon the single curvature trajectory, a kinematics model of a mobile robot is proposed to follow and capture the moving object, in this paper. A capturing scenario can be summarized as follows: 1. Motion of the moving object has been captured by a CCD camera., 2. Position of the moving object has been estimated using the image frames, and 3. The mobile robot tries to follow the moving object along the single curvature trajectory which matches positions and orientations of the moving object and the mobile robot at the final moment. Effectiveness of the single curvature trajectory modeling and capturing algorithm has been proved, through simulations and real experiments using a 2-DOF wheel-based mobile robot.

MPC Based Feedforward Trajectory for Pulling Speed Tracking Control in the Commercial Czochralski Crystallization Process

  • Lee Kihong;Lee Dongki;Park Jinguk;Lee Moonyong
    • International Journal of Control, Automation, and Systems
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    • v.3 no.2
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    • pp.252-257
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    • 2005
  • In this work, we propose a simple but efficient method to design a target temperature trajectory for pulling speed tracking control of the crystal grower in the Czochralski crystallization process. In the suggested method, the model predictive control strategy is used to incorporate the complex dynamic effect of the heater temperature on the pulling speed into the temperature trajectory design quantitatively. The feedforward trajectories designed by the proposed method were implemented on 200 mm and 300 mm silicon crystal growers in the commercial Czochralski process. The application results have demonstrated its excellent and consistent tracking performance of pulling speed along whole bulk crystal growth.