Precision improvement of MEMS gyros for indoor mobile robots with horizontal motion inspired by methods of TRIZ

Shin, Dongmyoung; Park, Sung Gil; Song, Byung Soo; Kim, Eung Su; Kupervasser, Oleg; Pivovartchuk, Denis; Gartseev, Ilya; Антипов, О.Л.; Kruchenkov, Evgeniy; Milovanov, Alexey; Kochetov, A. V.; Sazonov, Igor; Nogtev, Igor; Hyun, Sun Woo

doi:10.1109/nems.2014.6908769

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…In this paper, we describe correct operation of autopilot for supply desirable drone flight (movement of a drone in a vertical plane at a constant height). For the finding drone, flight parameters were used vision-based navigation [11][12][13][14][15][16][17][18][19][20]. For realization vision-based navigation was developed the computer program "Video-navigation of UAV over relief" [11].…”

Section: The Adaptation Of This Mathematical Theory For Dronementioning

confidence: 99%

A method for stabilization of drone flight controlled by autopilot with time delay

et al. 2020

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In this paper, the methods of the stability theory of differential equations with time delays are used in the study of an actual engineering problem of a drone (UAV) autonomous flight. We describe correct operation of autopilot for supply stability of desirable drone flight. There exists a noticeable delay in getting information about position and orientation of a drone to autopilot in the presence of vision-based navigation (visual navigation). In spite of this fact, we demonstrate that it is possible to provide stable flight at a constant height in a vertical plane. We describe how to form relevant controlling signal for autopilot in the case of the navigation information delay and provide control parameters for particular case of flight.

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Section: The Adaptation Of This Mathematical Theory For Dronementioning

confidence: 99%

A method for stabilization of drone flight controlled by autopilot with time delay

et al. 2020

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“…Two common approaches for the navigation problem are the landmarks [11,12]. And the ego-motion integration [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Robust Positioning of Drones for Land Use Monitoring in Strong Terrain Relief Using Vision-Based Navigation

Kupervasser

Sarychev²,

Rubinstein³

et al. 2018

GEOMATE

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For land use monitoring, the main problems are robust positioning in urban canyons and strong terrain reliefs with the use of GPS system only. Indeed, satellite signal reflection and shielding in urban canyons and strong terrain relief results in problems with correct positioning. Using GNSS-RTK does not solve the problem completely because in some complex situations the whole satellite's system works incorrectly. We transform the weakness (urban canyons and strong terrain relief) to an advantage. It is a vision-based navigation using a map of the terrain relief. We investigate and demonstrate the effectiveness of this technology in Chinese region Xiaoshan. The accuracy of the vision-based navigation system corresponds to the expected for these conditions. It was concluded that the maximum position error based on vision-based navigation is 20m and the maximum angle Euler error based on vision-based navigation is 0.83 degree. In case of camera movement, the maximum position error based on vision-based navigation is 30m and the maximum Euler angle error based on vision-based navigation is 2.2 degrees.

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“…With the current state of the art of MEMS technology, the accuracy of gyroscopes is not good enough for deriving heading estimation over longer terms because of their large biases and scale factors [ 27 , 28 ]. An effective method of minimizing drift in the heading estimation that relies solely on integration of rate signals from a gyro was examined to meet the challenges of making low-cost MEMS gyroscopes for the precise self-localization of indoor mobile robots [ 28 , 29 ]. Ali et al proposed to use a Kalman filter algorithm of fusing low-cost MEMS gyroscope and magnetometer in a smartphone to obtain heading estimation with quaternion mechanization [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

“…To meet the requirements of accurate indoor heading estimation using a low-cost MEMS strapdown inertial navigation system, an effective method of quaternion-based UKF algorithm has been proposed. The quaternion-based UKF algorithm has the following advantages over the general Kalman filter and EKF [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 42 , 43 , 44 , 45 , 46 ]: (1) The quaternion-based orientation of an object has no singularities when the pitch angle passes through ± π /2 than Euler angles or Direction Cosine Matrix (DCM); (2) Quaternion-based matrix transformation has higher computational efficiency than Euler angles and DCM, and it is more suitable for our low cost MEMS multi-sensor system; (3) EKF models are linearized through a first order Taylor series expansion of the process/measurement models around the current state estimate, meanwhile, Jacobian matrix computation is quite complex; but UKF is second order approximation, which has capability of dealing with large and small attitude errors.…”

Section: Introductionmentioning

confidence: 99%

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

Yuan

Zhang

et al. 2015

Sensors

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Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path.

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Precision improvement of MEMS gyros for indoor mobile robots with horizontal motion inspired by methods of TRIZ

Abstract: − In the paper, the problem of precision improvement for the MEMS gyrosensors on indoor robots with horizontal motion is solved by methods of TRIZ ("the theory of inventive problem solving").

Cited by 6 publications

References 16 publications

A method for stabilization of drone flight controlled by autopilot with time delay

A method for stabilization of drone flight controlled by autopilot with time delay

Robust Positioning of Drones for Land Use Monitoring in Strong Terrain Relief Using Vision-Based Navigation

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

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