• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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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.

• The Journal of Korea Robotics Society
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• v.8 no.1
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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.

• The Journal of Korea Robotics Society
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• v.6 no.4
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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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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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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• v.6 no.6
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.63-70
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• 2006

Due to the small size and weight of micro aerial vehicle (MAV), only miniaturized MEMS type sensors are applicable for MAV autonomous flight system. In this paper, we propose a accelerometer and gyro mixing algorithm to improve an attitude performance of MEMS type sensors. The performance of the proposed mixing algorithm is compared with the performance of fuzzy-based mixing algorithm through simulation. The simulation results show that the attitude compensation method through the attitude compensation has better performance than the fuzzy-based mixing method for MAV attitude estimation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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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.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2003.04a
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• pp.115-134
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• 2003

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.8
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• pp.16-21
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• 2012

The gyro sensor that made by MEMS process is generated an accumulated error(drift) and escape the zero angle following during calculation of rotate angle. This study propose BACF(Boot Angle Compensation Filter) algorithm for prevent escape zero angle and DCF algorithm for remove accumulated error. DCF algorithm is designed for acquire accurate turn of ratio by remove offset and noise components. BACF algorithm is obtained average offset that removed noise components by recursively calculate. Experimental environment, two-axis gyro sensor and mobile OIS camera mounted control board and 5Hz oscillation of ${\pm}0.5^{\circ}$ for the experiments were carried out. BACF and DCF algorithm is applied and the resulting accumulated error did not occur and exactly zero angle following results were made.