• IEIE Transactions on Smart Processing and Computing
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• 제6권1호
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• pp.1-9
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• 2017

This paper proposes to improve the performance of a strap down inertial navigation system using a foot-mounted low-cost inertial measurement unit/magnetometer by configuring an attitude and heading reference system. To track position accurately and for attitude estimations, considering different dynamic constraints, magnetic measurement and a zero velocity update technique is used. A conventional strap down method based on integrating angular rate to determine attitude will inevitably induce long-term drift, while magnetometers are subject to short-term orientation errors. To eliminate this accumulative error, and thus, use the navigation system for a long-duration mission, a hybrid configuration by integrating a miniature micro electromechanical system (MEMS)-based attitude and heading detector with the conventional navigation system is proposed in this paper. The attitude and heading detector is composed of three-axis MEMS accelerometers and three-axis MEMS magnetometers. With an absolute algorithm based on gravity and Earth's magnetic field, rather than an integral algorithm, the attitude detector can obtain an absolute attitude and heading estimation without drift errors, so it can be used to adjust the attitude and orientation of the strap down system. Finally, we verify (by both formula analysis and from test results) that the accumulative errors are effectively eliminated via this hybrid scheme.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• International Journal of Control, Automation, and Systems
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• 제4권1호
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• pp.1-9
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• 2006

This paper presents the modeling and multivariable feedback control of a novel high-precision multi-dimensional positioning stage. This integrated 6-degree-of-freedom. (DOF) motion stage is levitated by three aerostatic bearings and actuated by 3 three-phase synchronous permanent-magnet planar motors (SPMPMs). It can generate all 6-DOF motions with only a single moving part. With the DQ decomposition theory, this positioning stage is modeled as a multi-input multi-output (MIMO) electromechanical system with six inputs (currents) and six outputs (displacements). To achieve high-precision positioning capability, discrete-time integrator-augmented linear-quadratic-regulator (LQR) and reduced-order linearquadratic-Gaussian (LQG) control methodologies are applied. Digital multivariable controllers are designed and implemented on the positioning system, and experimental results are also presented in this paper to demonstrate the stage's dynamic performance.

• Korean Journal of Geomatics
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• 제2권1호
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• pp.17-24
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• 2002

The Global Positioning System technology has been widely used in positioning and attitude determination. It is well known that the accuracy, availability and reliability of the positioning results are heavily dependent on the number and geometric distribution of tracked GPS satellites. Because of this limitation, in some situations, such as in urban canyons, underground or inside of buildings, it is difficult to navigate with GPS receiver. Therefore, in order to improve the performance of satellite-based positioning, the integration of GPS with the pseudolite technology has been proposed. With this pseudolite technology, it is expected that seamless positioning service can be provided in a wider area without replacing existing GPS receivers. On the other hand, to adopt pseudolites on a larger scale, it is necessary to verify how the pseudolites may complement the existing GPS-based positioning. In this paper the authors present the details of the experiments and the results of the fundamental verification for seamless positioning using integration of GPS and pseudolite. This paper shows that the accuracy and efficiency of integrating GPS and pseudolite through the dynamic and static positioning experiment. The influence of pseudolite signal on GPS receiver is also discussed. The experimental results indicate that the accuracy of the height component can indeed be significantly improved, to approximately the same level as the horizontal component.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2002년도 창립 20주년기념 국제학술대회
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• pp.77-84
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• 2002

The Global Positioning System, GPS technology has been widely used in positioning and attitude determination. It is well known that the accuracy, availability and reliability of the positioning results are heavily dependent on the number and geometric distribution of tracked GPS satellites. Because of this limitation, in some situations, such as in urban canyons, underground space or inside of buildings, it is really hard to navigate with GPS receiver. Therefore, in order to improve the performance of satellite-based positioning, the integration of GPS with the pseudolite technology has been proposed. With this pseudolite technology, it is expected that seamless positioning service can be provided in wider area without replacing existing GPS receivers. On the other hand, to adopt pseudolites at larger scale, it is necessary to verify how the pseudolites can complement the existing GPS-based positioning. In this paper the authors present the detail of experimental investigations and the results of the fundamental verification for seamless positioning using integration of GPS and pseudolite. This paper shows that the accuracy and efficiency of integrating GPS and pseudolite through the dynamic and static positioning experiment and discuss about the influence on GPS receiver by pseudolite signal. The experimental results indicate that the accuracy of the height component can indeed be significantly improved, to approximately the same level as the horizontal component.

• 대한공간정보학회지
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• 제4권2호
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• pp.47-54
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• 1996

동체의 3차원 순간위치결정을 위해서는 동일시간에 획득한 2개 이상의 영상이 필요하다. 최근 대중화되고 있는 디지털 카메라를 이용할 수도 있겠으나 연속영상은 얻을 수 없으므로 본 연구에서는 이를 위하여 비디오카메라를 이용한 저가의 순간영상획득시스템을 구축하였다. 또한 동일한 시간대의 입체영상을 얻기 위하여 LCD타이머를 동체와 함께 촬영하고 얻어진 연속영상으로부터 비디오 편집기를 이용하여 독립수치영상을 얻었다. 그 결과 동일시간의 수치영상을 $788{\times}550$픽셀의 해상도로 얻을 수 있었고 1/100sec의 시간정확도로 획득한 동체상의 타겟을 검사 한 결과 양호하였다. 추후 3차원 위치정확도를 비교하기 위해 일반 측정용사진기로 B-shutter를 이용하여 동체를 촬영, 양호한 음화를 획득할 수 있었다.

• Ocean Systems Engineering
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• 제12권4호
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• pp.461-477
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• 2022

Dynamic Positioning (DP) is a system that uses computer-controlled thrusters, propellers, and other propulsion devices to automatically maintain a vessel's position and heading. In this study, a wind turbine installation vessel with DP capabilities was proposed for use in mild environmental conditions in the Yellow Sea. The thruster arrangements of the vessel were analyzed in relation to wind and current loads, and it was found that a four-corner arrangement of thrusters provided the best position-keeping performance. The vessel's DP control performance was also analyzed in relation to the increased environmental load caused by the presence of a wind turbine, using a capability plot. The vessel's performance was evaluated in three different states: floating with no load, during the loading of a wind turbine and suction buckets, and after the wind turbine has been installed. The use of 750 kW and 1,000 kW thrusters was also considered, and the environmental loads in the Saemangeum coastal area and the environmental load when a 5-Megawatt wind turbine is on board were assessed. The study concluded that at least four thrusters should be used for DP to safely manage the installation process of wind turbines.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.219-223
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• 2006

This paper presents a gantry type 3-axes positioning system, which is useful to test control algorithms for coordinate measuring machines and industrial cranes. The dynamic characteristics of the system have been investigated through a series of finite element analysis and experiments. In order to minimize the residual vibration during movement, this paper implements input shaping algorithms for the system with the information from the dynamic analysis. The results show that the dynamic performance of the system can be significantly improved by the dynamic analysis and implementation of input shaping

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.