• 드라이브 ㆍ 컨트롤
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• 제13권1호
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• pp.49-53
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• 2016

The accurate calculation of bucket tip position has a large influence on showing the motion of an excavator on the display device of the excavator and controlling the excavator automatically. It is generally known that Inertial Measurement Unit (IMU) sensors are more accurate than accelerometer-based sensors while the boom, arm or bucket moves because additional forces beyond gravity add additional acceleration to the sensors. To prove the accuracy difference between the two types of sensors, a position recognition system using an accelerometer-based sensor and an IMU sensor is implemented on the excavator. The experimental results show that the system using the IMU sensor significantly reduces the position recognition error while bucket moves and additional force beyond gravity exists.

• International Journal of Ocean System Engineering
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• 제1권3호
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• pp.165-170
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• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.

• 대한공간정보학회지
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• 제20권1호
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• pp.65-72
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• 2012

MEMS(Micro Electro Mechanical System)기술이 발전하여 작고 저렴한 IMU(Initial Measurement Unit)와 GPS(Global Positioning System)통합센서가 생산되어 다양한 분야에서 활용되고 있다. 본 연구에서는 모바일매핑시스템을 경량화하기 위해서 MEMS 기반 IMU/GPS 통합센서가 적합할 것으로 판단하고 XSens사 MEMS 기반 IMU/GPS 통합센서(MTi-G)의 특성 분석을 위한 실험을 수행하였다. 차량 대시보드에 통합센서를 고정하고 인천 송도 국제도시 도로구간과 터널구간을 주행하여 후처리 과정을 거치지 않은 좌표성과를 취득하였다. 전반적으로 위치결정 성과가 양호했지만 일부 구간(정지구간, 과속방지턱, 터널구간 등)에서 센서 특성, XKF(칼만필터) 특성 및 GPS 신호 수신환경 제한으로 인해 양호하지 못한 부분이 확인되었다. 실험결과 경량 모바일매핑시스템의 활용 가능성을 확인할 수 있었으며, 향후 다양한 GPS 신호 수신환경과 주행 조건에서의 실험과 보다 정밀한 정확도 분석이 요구된다.

• 센서학회지
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• 제25권3호
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• pp.202-207
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• 2016

Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.

• 한국항공우주학회지
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• 제32권10호
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• pp.53-59
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• 2004

저급 관성센서로 구성된 중첩 IMU의 오차 보정 기법을 제안한다. 고장 검출 및 분리 기능을 갖는 중첩 IMU의 오차 보상을 위하여 먼저 IMU 내부의 기본 좌표계를 정의하고 그 좌표계상에서 오차 모델을 유도한다. 오차 계수를 추정하기 위한 수식을 정립하고 원추 배치를 갖는 중첩 IMU의 오차 보상을 위해 2축 레이트 테이블의 시험 순시를 제시한다. 그리고 제안된 오차 보상 기법의 성능을 검증하기 위하여 저급 관성센서를 사용하여 원추 배치 중첩 IMU를 구현하고 오차 계수를 추정, 보상한다.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• 대한조선학회논문집
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• 제56권5호
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• pp.439-446
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• 2019

A real time transporter locating system for shipyard has been implemented through the GNSS and IMU sensor. There are a lot of block movements by transporters at the shipyard, which need to be controlled and monitored for conforming to the shipbuilding process. For the precise and safe transporter motion at the yard, a locating system has been developed by using the GNSS and IMU sensors for the transporter. There are several obstacles of the GPS signals for locating the transporter at the yard, such as, buildings and metal structures. To overcome the weakness of the GPS signal transmission, the IMU data have been properly integrated together. The performance of the proposed real time block locating system has been verified through the real experiments with transporters carrying blocks at a shipyard.

• 한국멀티미디어학회논문지
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• 제22권9호
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• pp.1011-1019
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• 2019

In this paper, we propose a system that can more precisely identify and monitor the position of the tool used in the assembling workplace such as automobile production. The proposed positioning monitoring system is a combination of UWB communication module and MEMS IMU sensor. Since UWB does not need modulation and demodulation function and has low power density, UWB is widely used in indoor positioning field. However, it may cause positioning error due to errors in RF transmission and reception process, which may cause positioning accuracy. Therefore, in this paper, we propose an algorithm that uses IMU as an auxiliary means to compensate for errors that may occur in positioning using only UWB. The tag and anchor of UWB module measure the transmission / reception time by transmitting signals to each other and then estimate the distance between tag and anchor. The MEMS IMU sensor serves to provide positioning calibration information. The tag, which is a mobile node and attached to a moving tool, measures the three-dimensional position of the tool and transfers the coordinate data to the anchor. Thus, it is possible to confirm whether or not the specific tool is properly used according to the prescribed regulations.

• 전자공학회논문지 IE
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• 제45권4호
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• pp.11-18
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• 2008

본 연구는 다족 로봇용 자세제어장치(ACS - Attitude Control System)인 관성측정 시스템(IMU) 의 H/W 설계와 자세제어 알고리즘 S/W을 설계하여 다관절용 로봇의 IMU 통합시스템을 구현 후 이 시스템의 동작성능을 검증하기 위해 Mtx와 MTx와의 성능을 비교 검증을 하고자 한다. ACS는 자이로와 가속도계 그리고 지자기 센서를 이용하여 항체의 롤, 피치각 자세를 제어하는 시스템이다. 일반적인 저가형 MEMS 관성센서로는 오차가 심하게 발생하여 항체의 정확한 위치를 계산하기 힘들다. 본 연구에서는 ACS 개발하기 위하여 상용의 MEMS 가속도계 및 자이고 센서, 추가적으로 지자기 센서를 사용하여 관성측정 시스템(IMU)을 표현한다. 구현된 IMU 시스템에 자세계산 프로그램을 내장하여 일정 성능을 보장하는 롤, 피치, 요 자세각 알고리즘을 설계하여 시스템에 포팅한다. 본 연구에서는 자이로와 가속도계 출력을 혼합하여 롤, 피치각을 보상함으로써 지속적으로 일정 수준이상의 성능을 보장하는 ACS를 구현하기위해 목표 플랫폼에 적재하여 실시간으로 구동하여 포팅하고 검증하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.525-528
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• 2003

In this paper, we present a novel idea to integrate low cost Inertial Measurement Unit(IMU) and Differential Global Positioning System (DGPS) for Telematics applications. As well known, low cost IMU produces large positioning and attitude errors in very short time due to the poor quality of inertial sensor assembly. To conquer the limitation, we present a bimodal approach for integrating IMU and DGPS, taking advantage of positioning and orientation data calculated from CCD images based on photogrammetry and stereo-vision techniques. The positioning and orientation data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method that can provide accurate position and attitude information for extended period for non-aided GPS information.