• 제어로봇시스템학회논문지
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• 제13권10호
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• pp.970-977
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• 2007

Absolute position detector which is one of the major equipment in the field of factory automation, not only perceives the absolute position of the rotary machine but also outputs switch data according to the given angle. Absolute position detector is composed of sensor module and its controller. In this paper, a sensor driver is implemented using FPGA with VHDL. This chip has a less form factor than conventional circuit. A test shows reliable precision within THD(total harmonic distortion) of 0.2% which can be applicable commercially. Also, FPGA-based phase error compensation methods were newly discussed. In the future, more research will be conducted to enhance the precision by the introduction of 3-phase transformer.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.119-124
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• 2013

Recent increasing demand on the indoor localization requires more advanced and hybrid technology. This paper proposes an application of the hybrid indoor localization method based on a position-coded pattern that can be used with other existing indoor localization techniques such as vision, beacon, or landmark technique. To reduce the pattern-recognition error rate, the error detection and correction algorithm was applied based on Hamming code. The indoor localization experiments based on the proposed algorithm were performed by using a QCIF-grade CMOS sensor and a position-coded pattern with an area of $1.7{\times}1.7mm^2$. The experiments have shown that the position recognition error ratio was less than 0.9 % with 0.4 mm localization accuracy. The results suggest that the proposed method could be feasibly applied for the localization of the indoor mobile service robots.

• Current Optics and Photonics
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• 제5권4호
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• pp.362-369
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• 2021

Absolute position sensors are widely used in machine tools and precision measuring instruments because measurement errors are not accumulated, and position measurements can be performed without initialization. The laser speckle-based absolute position sensor, in particular, has advantages in terms of simple system configuration and high measurement accuracy. Unlike traditional absolute position sensors, it does not require an expensive physical length scale; instead, it uses a laser speckle image database to measure a moving surface position. However, there is a problem that a huge database is required to store information in all positions on the surface. Conversely, reducing the size of the database also decreases the accuracy of position measurements. Therefore, in this paper, we propose a new method to measure the surface position with high precision while reducing the size of the database. We use image stitching and approximation methods to reduce database size and speed up measurements. The absolute position error of the proposed method was about 0.27 ± 0.18 ㎛, and the average measurement time was 25 ms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.584-586
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• 2005

In this paper, low cost inertial sensor and compass were used instead of encoder for localization of mobile robot. Movements by encoder, movements by inertial sensor and movements by complementary filter with inertial sensor and compass were analyzed. Movement by complementary filter was worse than by only inertial sensor because of imperfection of compass. For the complementary filter to show best movements, compass need to be compensated for position error.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.

• 제어로봇시스템학회논문지
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• 제19권4호
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• pp.372-378
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• 2013

In this paper, we research the localization problem of the crawler-type inspection robot for underwater structure which travels an outer wall of underwater structure. Since various factors of the underwater environment affect an encoder odometer, it is hard to localize robot itself using only on-board sensors. So in this research we used a depth sensor and an IMU to compensate odometer which has extreme error in the underwater environment through using Extended Kalman Filter(EKF) which is normally used in mobile robotics. To acquire valid measurements, we implemented precision sensor modeling after assuming specific situation that robot travels underwater structure. The depth sensor acquires a vertical position of robot and compensates one of the robot pose, and IMU is used to compensate a bearing. But horizontal position of robot can't be compensated by using only on-board sensors. So we proposed a localization algorithm which makes horizontal direction error bounded by using kinematics relationship. Also we implemented computer simulations and experiments in underwater environment to verify the algorithm performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.533-535
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• 2006

Cleaning robot that is selling in present city has various cleaning algorithm. However, error of most products happens on progress direction by small obstacle that do not properly and miss cleaning thereby happens. There is robot that correct own position, but is hard to use in general home because economical strain is very big because is high price product very. In this paper measures angular velocity of robot using deviation sensor, and do to correct error using turning angular velocity and vertical angular velocity. Because detailed cleaning such as high pice style is available without addition of expensive hardware in middle and low price style cleaning product thereby, can possess price competitive power.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• 한국지능시스템학회논문지
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• 제21권2호
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• pp.178-185
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• 2011

본 논문은 상태변수 평준화 및 되먹임구조를 이용하여 무인잠수정의 위치추정을 개선하기 위한 다중센서 융합 기반의 위치추정 알고리즘을 제안한다. 이를 위해 먼저 상대적으로 오차가 큰 주 센서인 INS와 오차가 작은 보조센서인 DVL에서 측정되는 상태변수를 예측단계 이전에 융합하여 상태변수 평준화 과정을 수행한다. 그 다음, 평준화된 상태변수를 각 필터에 입력하여 예측 및 수정단계의 칼만 필터링 과정을 통해 최종 수정된 상태변수를 융합시키며, 마지막으로 이를 다시 주센서에 되먹임함으로서 무인잠수정의 위치추정을 개선한다. 평가를 위해 무인잠수정의 기동모델에 대한 시뮬레이션을 실시하여 기동경로를 생성하고 제안 알고리즘을 적용하여 위치추정 성능을 확인한다. 평가 결과, 제안 알고리즘이 다중센서 융합 알고리즘 중 가장 우수한 위치추정 성능을 보였으며, 또한 기동침로가 변경되는 구간에서도 강인한 위치추정이 가능하다는 것이 증명되었다.

• International Journal of Aeronautical and Space Sciences
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• 제12권1호
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• pp.24-36
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• 2011

A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.