• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.91-92
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• 2018

고령화 사회로 접어들기 시작하면서 최근 안전에 대한 많은 문제가 떠오르고 있다. 또한 노인의 안전 및 복지에 관한 법률 및 제품들이 출시되고 있는 상황이다. 따라서 본 논문에서는 노인의 안전에 관한 조사를 진행하였다. 노인의 상해의 주요인으로는 찰과상 및 타박상 또는 낙상사고가 있으며, 이러한 요인을 해결하고자 본 논문에서는 자이로 센서와 가속도 센서를 활용하여 노인의 넘어짐 또는 미끄러짐과 같은 동작을 인지 할 수 있는 시스템에 대해 연구를 진행하였다.

• 한국측량학회지
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• 제32권3호
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• pp.253-259
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• 2014

There has been a need for replacing human labors with a robot in such dangerous and hard jobs of various construction sites. For that reason, many researches have been made about the high quality robot, which performs its duty instead of human labors. This study is about auto surveying system development based on VRS-GPS which enables autodriving in dangerous areas where it's difficult for humans to measure directly. This study is about the auto-surveying system development, based on VRS-GPS, which enables auto-drive in dangerous areas, whereas difficult for humans to measure directly. The GPS is made with GRXI and SHC250 controllers of the SOKKIA company. The auto surveying system is composed of DPS module, geomagnetism sensor, bluetooth, gimbals, IMU, etc to automatic drive via enter into a route of position. The developed auto surveying system has installed the carmeras for front and vertical axis as well as systems to grasp situation of surveying with smartphone in real time. The result from analysed RMSE of auto surveying system and VRS-GPS surveying is 0.0169m of X-axis and 0.0246m of Y-axis.

• 센서학회지
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• 제28권1호
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• pp.30-35
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• 2019

Inertial measurement units (IMUs) are widely used for wearable motion-capturing systems in the fields of biomechanics and robotics. When the IMUs are combined with optical motion sensors (hereafter, OPTs) for their complementary capabilities, it is necessary to align the coordinate system orientations between the IMU and OPT. In this study, we compare the application of two coordinate transformation-based orientation alignment methods between two coordinate systems. The first method (M1) applies angular velocity coordinate transformation, while the other method (M2) applies gyroscopic angle coordinate transformation. In M1 and M2, the angular velocities and angles, respectively, are acquired during random movement for a least-square algorithm to determine the alignment matrix between the two coordinate systems. The performance of each method is evaluated under various conditions according to the type of motion during measurement, number of data points, amount of noise, and the alignment matrix. The results show that M1 is free from drift errors, while drift errors are present in most cases where M2 is applied. Thus, this study indicates that M1 has a far superior performance than M2 for the alignment of IMU and OPT coordinate systems for motion analysis.

• 전기학회논문지
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• 제66권1호
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• pp.121-126
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• 2017

Tracking system is essential for Image Guided Surgery(IGS). Optical Tracking System(OTS) is widely used to IGS for its high accuracy and easy usage. However, OTS doesn't work when occlusion of marker occurs. In this paper sensor data fusion with OTS and Inertial Navigation System(INS) is proposed to solve this problem. The proposed system improves the accuracy of tracking system by eliminating gaussian error of the sensor and supplements the disadvantages of OTS and IMU through sensor fusion based on Kalman filter. Also, sensor calibration method that improves the accuracy is introduced. The performed experiment verifies the effectualness of the proposed algorithm.

• 예술인문사회 융합 멀티미디어 논문지
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• 제7권1호
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• pp.177-186
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• 2017

최근 무인자동차가 큰 관심을 받고 있다. 세계 최대 규모의 온라인 쇼핑 서비스업체인 아마존은 드론을 활용한 배송시스템을 개발하고 있다. 이러한 플랫폼의 항법을 위해서는 정확한 자세정보가 필요하다. 본 논문에서는 저가형 관성센서를 활용한 AHRS 구조 설계를 제안하였다. 쿼터니언기반의 운동방정식, 바이어스가 제거된 자이로 측정치, MEMS 가속도계와 지자기 센서를 이용하여 자세를 추정하는 칼만 filter를 설계하였다. MEMS 자이로의 바이어스를 제거하기 위하여 자이로 측정치와 자세 추정치를 이용하는 자이로 바이어스 제거용 칼만 filter를 추가하였다. 구현한 AHRS의 성능을 고가의 상용 Microstrain사의 3DM-GX3-25 AHRS와 비교 실험을 통하여 칼만 filter가 자이로의 바이어스 오차를 0.0001[deg/s]이하로 추정함을 볼 수 있었다. 또한 최종적으로 구해진 자세에서 롤각과 피치각은 0.2, 0.3[deg]이내의 오차를 보여주었다. 요 각은 6[deg] 이하의 오차가 발생하였다.

• International Journal of Aeronautical and Space Sciences
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• 제11권3호
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• pp.234-239
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• 2010

The utilization of micro-electro-mechanical system (MEMS) gyros and accelerometers in low-level inertial measurement unit (IMU) influences cost effectiveness in a positive way under the condition that device error characteristics are fully calibrated. The conventional calibration process utilizes a rate table; however, this paper proposes a new method for achieving reference calibration data from the natural motion of pendulum to which the IMU undergoing calibration is attached. This concept was validated with experimental data. The pendulum angle measurements correlate extremely well with the solutions acquired from the pendulum equation of motion. The calibration data were computed using the regression method. The whole process was validated by comparing the measurement from the 6 sensor components with the measurements reconstructed using the identified calibration data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.141.5-141
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• 2001

An attitude GPS receiver with 3 antennas obtains 3-dimensional attitude using GPS carrier phase measurement INS obtains the 3 dimensional navigation solution for IMU consisting of accelerometers and gyro. Ground-alignment process for the low -cost INS cannot be performed well due to the large sensor noise. Using the standard GPS receiver, however, continuous in-flight alignment for the INS becomes possible, and consequently, the errors in IMU sensors and navigation solution can be compensated. Especially with attitude measurement from the attitude GPS receiver, the compensation of errors in gyroscope and attitude would be done respite of the vehicle´s dynamics and their error covariance would be reduced. This paper presents ...

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.133-139
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• 2007

An unmanned ground vehicle can perform its mission automatically without human control in unknown environment. To move up to a destination in various surrounding situation, navigational information is indispensible. In order to be adopted for an unmanned vehicle, the navigation box is small, light weight and low power consumption. This paper suggests navigation system using a low grade MEMS IMU for supplying position, velocity, and attitude of an unmanned ground vehicle. This system consists of low cost and light weight MEMS sensors and a GPS receiver to meet unmanned vehicle requirements. The sensors are basically integrated by loosely coupled method using Kalman filter and internal algorithms are divided into initial alignment, sensor error compensation, and complex navigation algorithm. The performance of the designed navigation system has been analyzed by real time field test and compared to commercial tactical grade GPS/INS system.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2015년도 하계학술대회
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• pp.540-541
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• 2015

본 논문은 카메라 촬영 시 손 떨림 등에 의해 생기는 불균일한 블러 현상에 대해 영상 IMU 센서와 노출시간이 긴 영상과 짧은 영상 쌍을 이용한 디블러 알고리즘을 제안한다. 먼저 IMU 센서로부터 얻어진 gyro 데이터로 초기 커널을 추정한다. 그런 다음 노출시간이 다른 영상 쌍에 Lucas-Kanade 기법을 적용하여 상기 추정된 초기 커널을 개선한다. 이렇게 구해진 커널에 기반하여 residual deconvolution 을 수행 디블러 영상을 생성한다. 실험 결과로부터 제안 알고리즘이 기존 기법에 비해 우수한 성능을 보임을 알 수 있다.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.