Thematische Bibliographien / BNO055

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Konferenzberichte

Auswahl der wissenschaftlichen Literatur zum Thema „BNO055“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 18. Februar 2022

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Zeitschriftenartikel zum Thema "BNO055"

1

Febriawan, Anggit, und Wahyu Sapto Aji. „Rotating Control on Robots Indonesian Abu Robot Contest with PID and IMUBNO055 Controls“. Buletin Ilmiah Sarjana Teknik Elektro 2, Nr. 1 (14.05.2020): 14. http://dx.doi.org/10.12928/biste.v1i3.987.

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One of the problems solved in robot control is that the required robot movement system can be moved efficiently. Controls used to increase the efficiency of robot motion are the PID (Proportional-Integral-Derivative) Control and the IMU BNO055 sensor. The concept used by the robot to be able to rotate to a certain angle entered the desired angle, then read the sensor angle BNO055 then the results of the sensor readings are sent to Arduino to then provide a signal to drive the motor. The results of research that has been done, the robot can display an angle of 0o and 180o in accordance with the sensor readings. The robot can rotate with a short effective time from 10 times of testing and with an average time of 2 seconds. From the research results, the robot can rotate to the desired angle effectively and the robot can choose the desired angle with the help of instructions with an average error of 0.88%. The best control parameter values are Kp = 1; Ki = 0,00095; and Kd = 4.Salah satu masalah yang dihadapi dalam kendali robot yaitu sistem gerakan robot yang mengharuskan dapat bergerak secara efisien. Kendali yang digunakan untuk meningkatkan efisiensi gerakan robot adalah dengan Kendali PID (Proporsional-Integral-Derivatif) dan sensor IMU BNO055. Konsep yang digunakan robot agar dapat berotasi ke sudut tertentu yaitu memasukkan sudut yang diinginkan, kemudian membaca sudut sensor BNO055 kemudian hasil dari bacaan sensor dikirim ke Arduino untuk selanjutnya memberikan sinyal untuk menggerakkan motor. Hasil penelitian yang sudah dilakukan, robot dapat menampilkan sudut 0o dan sudut 180o sesuai dengan pembacaan sensor. Robot dapat berotasi dengan efektif dengan waktu yang singkat dari 10 kali pengujian dan dengan rata – rata waktu yaitu 2 detik. Dari hasil penelitian robot dapat berotasi ke sudut yang diinginkan dengan efektif dan robot dapat menunjukkan sudut yang diinginkan dengan bantuan petunjuk dengan cukup baik dengan rata – rata error 0,88%. Nilai parameter pengendali terbaik adalah Kp=1; Ki=0,00095; dan Kd=4.
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2

Omidalizarandi, M., I. Neumann, E. Kemkes, B. Kargoll, D. Diener, J. Rüffer und J. A. Paffenholz. „MEMS BASED BRIDGE MONITORING SUPPORTED BY IMAGE-ASSISTED TOTAL STATION“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (18.10.2019): 833–42. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-833-2019.

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Abstract. In this study, the feasibility of Micro-Electro-Mechanical System (MEMS) accelerometers and an image-assisted total station (IATS) for short- and long-term deformation monitoring of bridge structures is investigated. The MEMS sensors of type BNO055 from Bosch as part of a geo-sensor network are mounted at different positions of the bridge structure. In order to degrade the impact of systematic errors on the acceleration measurements, the deterministic calibration parameters are determined for fixed positions using a KUKA youBot in a climate chamber over certain temperature ranges. The measured acceleration data, with a sampling frequency of 100 Hz, yields accurate estimates of the modal parameters over short time intervals but suffer from accuracy degradation for absolute position estimates with time. To overcome this problem, video frames of a passive target, attached in the vicinity of one of the MEMS sensors, are captured from an embedded on-axis telescope camera of the IATS of type Leica Nova MS50 MultiStation with a practical sampling frequency of 10 Hz. To identify the modal parameters such as eigenfrequencies and modal damping for both acceleration and displacement time series, a damped harmonic oscillation model is employed together with an autoregressive (AR) model of coloured measurement noise. The AR model is solved by means of a generalized expectation maximization (GEM) algorithm. Subsequently, the estimated model parameters from the IATS are used for coordinate updates of the MEMS sensor within a Kalman filter approach. The experiment was performed for a synthetic bridge and the analysis shows an accuracy level of sub-millimetre for amplitudes and much better than 0.1 Hz for the frequencies.
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3

Stanzani, Ronny, Paolo Dondero, Alfonso Mantero und Marco Testa. „Measurement Accuracy of an Upper Limb Tracking System Based on Two Hillcrest Labs BNO080 IMU Sensors: An Environmental Assessment“. IEEE Sensors Journal 20, Nr. 17 (01.09.2020): 10267–74. http://dx.doi.org/10.1109/jsen.2020.2992733.

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4

Hostanska, Katarina, Guido Jürgenliemk, Gudrun Abel, Adolf Nahrstedt und Reinhard Saller. „Willow bark extract (BNO1455) and its fractions suppress growth and induce apoptosis in human colon and lung cancer cells“. Cancer Detection and Prevention 31, Nr. 2 (Januar 2007): 129–39. http://dx.doi.org/10.1016/j.cdp.2007.03.001.

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Dissertationen zum Thema "BNO055"

1

Němec, Radek. „Systém pro ovládání počítačové prezentace s využitím gest“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442497.

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This thesis attempts with the design of a device for contactless control of the computer presentation. In the first part there are theoretically described the methods of contactless computer control. The second part is focused on the description of different types of sensors and also the key elements for this thesis – the development board TinyPICO ESP32 and sensor BNO055. Finally, in the third part there is described the design of the device and gestures.
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Diewald, Tobias [Verfasser], Wolfgang [Akademischer Betreuer] Wuttke, Sabine [Gutachter] Mihm und Martin [Gutachter] Oppermann. „Effekt von Estradiol und Cimicifuga racemosa (C001) BNO1055 und deren Subfraktionen (C001/S1-S3, R1-R3) auf das Fett- und Muskelgewebe sowie auf Serumparameter der ovarektomierten Ratte / Tobias Diewald ; Gutachter: Sabine Mihm, Martin Oppermann ; Betreuer: Wolfgang Wuttke“. Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2016. http://d-nb.info/1119447356/34.

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3

YANG, REN-HAO, und 楊仁濠. „A Study on Soccer Ball Tracing Based on Kalman Filter Using BNO055 Motion Sensor“. Thesis, 2018. http://ndltd.ncl.edu.tw/handle/6594md.

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碩士
玄奘大學
資訊管理學系碩士班
106
With the continuous advancement of low-power Bluetooth wireless transmission and sensor technology, this paper proposes a scheme for analyzing the trajectory of football. It is to embed an integrated multi-axis sensor inside football to collect relevant motion information, and then correct the collected information via Kalman filter to track and analyze football trajectory. Most sport’s competitions have the characteristics of rapid rhythm and open field characteristics, which intensifies the complexity of the entire game and increases the difficulty of analysis of the game. This thesis mainly analyzes the dynamic trajectory of the dribble on the training of football players. We firstly record the acceleration and rotation quaternion of the sensor. The difference in the rotation angle between the displacement integral and the sphere itself on the geomagnetic azimuth allows us to obtain the trajectory analysis of the dribble process. Sensors detected at the next moment have a very strong correlation with the current detection value. Therefore, we first use the Kalman filter to correct the relevant information. The test data is that the professional different football players dribble back and forth with the single-legged, two-legged and mixed kick control methods. Experimental results show that the number of strokes can be effectively and accurately obtained. However, there may still be considerable difficulties in the trajectory of the football due to uncertainties in the accuracy of the sensed values.
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Diewald, Tobias. „Effekt von Estradiol und Cimicifuga racemosa (C001) BNO1055 und deren Subfraktionen (C001/S1-S3, R1-R3) auf das Fett- und Muskelgewebe sowie auf Serumparameter der ovarektomierten Ratte“. Doctoral thesis, 2016. http://hdl.handle.net/11858/00-1735-0000-002B-7C47-5.

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Konferenzberichte zum Thema "BNO055"

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Tian, Yuan, und Marc Compere. „Monocular Visual Inertial Odometry (VIO) Dataset Collection With a Self-Calibrating Platform for Inertial Measurement Unit (IMU)“. In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10595.

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Abstract In this study, we built a monocular visual inertial odometry (VIO) dataset with a proposed self-calibrating platform for an inertial measurement unit (IMU). For a learning-based method, lack of database is the biggest limitation. One goal of this study is to generate a high-quality VIO database. Meanwhile, a properly calibrated inertial measurement unit (IMU) is critical for improving VIO system accuracy and precision. However, a professional IMU calibration tool is usually expensive and large. The proposed self-calibrating platform shows its benefits in eliminating the manual work in calibration and reducing the cost of the expensive platform, which brings more opportunities to students and researchers. This self-calibrating system was useful for collecting monocular visual inertial odometry datasets while driving. . The calibrated IMU generates 14 numbers at 100Hz: time, 3-axis accelerometer measurements, 3-axis gyroscope measurements, 3 Euler angles, and 4 quaternions. This VIO system is composed of a monocular camera, GoPro Hero 3, an IMU, BNO055, and a GPS, ANT-555. The sensors are mounted on a John Deere Gator™ Full-Size Crossover Utility Vehicle and are operated on an Intel NUC, a mini-size computer. The final dataset contains monocular images, IMU measurements, and GPS outputs.
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