• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.893-897
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• 2008

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing the drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is to use wavelet de-noising filter in order to reduce random noise which affects short-term performances. The proposed method was applied to Epson XV3500 gyro and the performances are verified by the comparisons with an existing commercial gyro module of vacuum cleaning robots.

• 로봇학회논문지
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• 제8권1호
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• pp.29-36
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• 2013

This paper presents a sensitivity optimization of a MEMS (microelectromechanical systems) gyroscope for a magnet-gyro system. The magnet-gyro system, which is a guidance system for a AGV (automatic or automated guided vehicle), uses a magnet positioning system and a yaw gyroscope. The magnet positioning system measures magnetism of a cylindrical magnet embedded on the floor, and AGV is guided by the motion direction angle calculated with the measured magnetism. If the magnet positioning system does not measure the magnetism, the AGV is guided by using angular velocity measured with the gyroscope. The gyroscope used for the magnet-gyro system is usually MEMS type. Because the MEMS gyroscope is made from the process technology in semiconductor device fabrication, it has small size, low-power and low price. However, the MEMS gyroscope has drift phenomenon caused by noise and calculation error. Precision ADC (analog to digital converter) and accurate sensitivity are needed to minimize the drift phenomenon. Therefore, this paper proposes the method of the sensitivity optimization of the MEMS gyroscope using DEAS (dynamic encoding algorithm for searches). For experiment, we used the AGV mounted with a laser navigation system which is able to measure accurate position of the AGV and compared result by the sensitivity value calculated by the proposed method with result by the sensitivity in specification of the MEMS gyroscope. In experimental results, we verified that the sensitivity value through the proposed method can calculate more accurate motion direction angle of the AGV.

• 로봇학회논문지
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• 제6권4호
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• pp.334-343
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• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.592-595
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• 2004

This paper presents a study on the development of a multi-sensing inertial sensor with a single mechanical structure, which can be used both as a gyroscope and an accelerometer. The proposed MEMS gyro-accelerometer is designed to detect the angular rate and the acceleration at the same time using two separate detection circuits for one proof mass. In this study, the detection and signal processing circuit for an effective signal processing of different inertial measurements is designed, fabricated, and tested. The experimental results show that the performances of the gyro-accelerometer have resolutions of 1mg and 0.025deg/sec and nonlinearities of less than 0.5% for the accelerometer and the gyroscope, respectively, which are similar results with those of sensors with different structures and different detection circuits. The size of the sensor is reduced almost by 50% comparing with the sensors of separated proof mass.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.873-883
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• 2008

This paper presents a parametric study on the controller design scheme for a gyro-accelerometer to have robust performance under some parameter variations. In particular, an integral and derivative based controller design method is suggested to achieve the desired performances of stability margin, bandwidth, and uniformity of scale for both gyroscopes and accelerometers with uncertainties of quality factor and resonant frequency. The simulation result shows that the control loop based on the suggested method gives satisfactory performance robustness under parameter variations, demonstrating the usefulness of the proposed design scheme.

• 한국항공우주학회지
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• 제34권8호
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• pp.63-70
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• 2006

초소형 비행체는 초소형, 초경량이기 때문에 매우 작고 가벼운 MEMS형 센서만이 초소형 비행체 자동 비행 장치에 적용될 수 있다. 본 논문에서는 이러한 MEMS 형 관성센서의 항법 성능을 향상시키기 위해 가속도계와 자이로를 혼합하는 알고리즘으로 자세 비교 보상을 이용한 혼합 방법을 제시하고 기존의 퍼지 추정을 이용한 혼합 방법과 시뮬레이션을 통해 성능을 비교한다. 이를 통하여 자세 비교 보상 방법을 이용한 혼합 방법이 기존의 퍼지를 기반으로 하는 혼합 방법보다 초소형 비행체 자세 추정에 보다 더 우수한 성능을 가짐을 보인다.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.470-476
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• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.

• 한국마이크로전자및패키징학회:학술대회논문집
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• 한국마이크로전자및패키징학회 2003년도 국제표면실장 및 인쇄회로기판 생산기자재전:전자패키지기술세미나
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• pp.115-134
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• 2003

• 대한전자공학회논문지SD
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• 제49권8호
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• pp.16-21
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• 2012

MEMS 기반의 자이로 센서는 회전 각도를 추출하는 과정에서 잡음성분에 의한 누적오차(drift) 및 영점(zero angle) 이탈현상이 발생한다. 본 연구에서는 이러한 누적오차를 제거하기 위한 DCF(Drift Compensatio Filter) 알고리즘과 각도 추출 시영점 이탈 방지를 위한 BACF(Boot Angle Compensation Filter) 알고리즘을 제안한다. DCF 알고리즘은 자이로 센서의 출력값에서 오프셋 및 잡음성분을 제거하여 순수 이동량을 얻을 수 있도록 설계한다. BACF 알고리즘은 자이로 센서로부터 출력되는 오프셋(Offset)에 포함된 잡음 성분을 재귀 평균법으로 계산하여 평균 오프셋을 구한다. 실험환경은 2축 자이로 센서 및 모바일 OIS 카메라가 탑재된 컨트롤 보드를 이용하여 5Hz의 ${\pm}0.5^{\circ}$의 진동에 대하여 BACF 및 DCF 알고리즘을 적용한 결과 누적 오차가 발생하지 않았으며, 영점 각도 추종이 정확히 이루어지는 결과를 확인하였다.