An initial research on Ultra-wideband and Inertial Measurement Unit pose estimation for Unmanned Aerial Vehicle

2016 ◽  
Author(s):  
Zheng Shuai-Yong ◽  
Fu Qiang ◽  
Hanna Tereshchenko ◽  
Wang Ti-Qiang ◽  
Quan Quan
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Pose Estimation ◽  
Inertial Measurement Unit ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Aerial Vehicle ◽  
Initial Research

scholarly journals Rancang Bangun Sistem Akuisisi Data Infra Merah Menggunakan Pesawat Udara Tanpa Awak (UAV) untuk Memantau Aktivitas Gunungapi

2020 ◽  
Vol 23 (1) ◽  
pp. 1
Author(s):  
Wahyudi Wahyudi ◽  
Kirbani Sri Brotopuspito ◽  
Imam Suyanto
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Aerial Vehicle

 Sebuah rancang bangun instrumen untuk sistem akuisisi data termal yang digunakan untuk pemantauan aktivitas gunungapi dengan meman-faatkan pesawat udara tanpa awak (UAV) telah dilakukan. Pesawat udara tanpa awak dipilih karena kemampuannya dalam menjangkau tubuh gunung dengan lebih mudah dan aman. Sensor infra merah digunakan sebagai muatan agar mampu mengukur suhu kawah dan permukaan gunungapi tanpa ada kontak langsung.       Sistem yang dibangun terdiri dari 3 perangkat utama, yakni sensor infra merah tipe Flir One Pro yang berfungsi sebagai kamera termal dan kamera visual, hand phone yang dilengkapi dengan software Redmi Note 5 yang berfungsi sebagai alat perekam data dan IMU (Inertial Measurement Unit), serta UAV (Unmanned Aerial Vehicle) yang berfungsi sebagai pesawat udara tanpa awak yang mengangkut sensor beserta alat perekam datanya.       Uji coba telah dilakukan baik di laboratorium maupun di lapangan. Uji coba pemetaan termal dilakukan di atas kawah G. Kelud pada ketinggian jelajah 100 m pada area seluas (100x300) m2 dengan laju rata-rata 15 m/s. Hasil uji coba menunjukkan bahwa sistem telah berfungsi dengan baik, meskipun terdapat kendala yang harus diperbaiki yang berkaitan dengan waktu melakukan pemetaan. Direkomendasikan agar pemetaan termal dilakukan pada malam hari sehingga obyek yang dipetakan mempunyai background termal yang relatif tetap, dan peta termal yang dihasilkan menjadi lebih konsisten.

scholarly journals SISTEM STABILISATOR ZERO ROLL PADA UAV (UNMANNED AERIAL VEHICLE) GLIDER

2020 ◽  
Vol 3 (2) ◽  
pp. 85
Author(s):  
Risqi Sugeng Putra Tama ◽  
Budhy Setiawan ◽  
Sidik Nurcahyo
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Time Constant ◽  
Inertial Measurement Unit ◽  
Settling Time ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Complementary Filter ◽  
Aerial Vehicle

Perkembangan teknologi robot terbang semakin pesat, hal ini ditandai dengan semakin banyak pemanfaatan robot terbang untuk membantu kerja manusia utamanya dalam bidang pengindraan jarak jauh salah satunya seperti evakuasi bencana. Penggunaan robot terbang blimp (balon udara) dan quadcopter pada area terbuka yang sedang terjadi bencana dinilai kurang efisien karena kestabilan roll blimp sangat rendah karena bentuknya yang besar dan ketahanan daya pada quad copter kurang optimal dikarenakan menggunakan empat motor penggerak untuk terbang. Solusi terbaik untuk mengatasi pengaruh gerakan angin terhadap kestabilan roll dan untuk memaksimalkan ketahanan daya dengan memanfaatkan angin yang datang adalah dengan menggunakan desain pesawat fixed wing berjenis glider yang terkontrol, dengan menerapkan kontrol PID dan megintegrasikan sensor Inertial Measurement Unit (Accelerometer dan Gyroscope) sehingga apabila terdapat gangguan angin dari arah samping kestabilan sudut roll pesawat saat terbang di udara dapat terkontrol dengan baik. Dari hasil percobaan yang diambil pada tanggal 20 Agustus 2016, robot terbang fixed wing dengan jenis glider dapat terbang di udara dengan baik dan dapat melakukan gerakan gliding secara crosswind (melawan angin) pada kecepatan angin ±4m/s. Pembacaan sensor IMU menggunakan metode complementary filter sudah optimal dengan nilai a sebesar 0,93, sehingga didapatkan time constant complementary filter sebesar 33,214ms. Penerapan algoritma PID kontroller dengan nilai variabel kp sebesar 1,2, ki sebesar 0,00005, kd sebesar 0.026  didapatkan hasil yang optimal, kontroller dapat menstabilkan posisi pesawat pada posisi nol derajat terhadap sumbu roll pada nilai hysterisis rata - rata antara 0,65 ° sampai -0,55 ° dengan nilai settling time  sebesar 300ms  serta  overshoot  sebesar -6,7 saat terjadi turbulensi udara.

scholarly journals Comparación de estrategias para la estimación de actitud en controladora de vuelo para UAV profesional

2021 ◽  
pp. 492-498
Author(s):  
David Gallarta Sáenz ◽  
Javier Rico-Azagra ◽  
Montserrat Gil-Martínez ◽  
Ramón Rico-Azagra
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Matlab Simulink ◽  
Inertial Measurement ◽  
Aerial Vehicle

Este trabajo presenta dos estrategias de integración multisensorial a través de las cuales se pretende encontrar un método apropiado para la estimación de actitud de un dron mediante filtros de Kalman y filtros complementarios explícitos. Para ello, se simulan los sensores de bajo coste, en concreto, unidades de medida inercial (IMU, Inertial Measurement Unit), que están incorporados en una controladora de vuelo diseñada para un UAV (Unmanned Aerial Vehicle) de ámbito profesional. De esta forma se dispone de unos datos fehacientes que resultan de gran interés para abordar la puesta en funcionamiento del sistema en pruebas reales, al poder implementar su sistema de control de forma adecuada en base a dicha información. La aplicación se desarrolla en MATLAB Simulink® por tratarse de un entorno adecuado para el trabajo con sistemas dinámicos.

scholarly journals A Robust and Adaptive Complementary Kalman Filter Based on Mahalanobis Distance for Ultra Wideband/Inertial Measurement Unit Fusion Positioning

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3435 ◽  
Author(s):  
Xin Li ◽  
Yan Wang ◽  
Kourosh Khoshelham
Keyword(s):  
Kalman Filter ◽  
Mahalanobis Distance ◽  
Inertial Measurement Unit ◽  
Least Squares Method ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Observation Error ◽  
System State ◽  
Inertial Measurement ◽  
The Impact

Ultra wideband (UWB) has been a popular technology for indoor positioning due to its high accuracy. However, in many indoor application scenarios UWB measurements are influenced by outliers under non-line of sight (NLOS) conditions. To detect and eliminate outlying UWB observations, we propose a UWB/Inertial Measurement Unit (UWB/IMU) fusion filter based on a Complementary Kalman Filter to track the errors of position, velocity and direction. By using the least squares method, the positioning residual of the UWB observation is calculated, the robustness factor of the observation is determined, and an observation weight is dynamically set. When the robustness factor does not exceed a pre-defined threshold, the observed value is considered trusted, and adaptive filtering is used to track the system state, while the abnormity of system state, which might be caused by IMU data exceptions or unreasonable noise settings, is detected by using Mahalanobis distance from the observation to the prior distribution. When the robustness factor exceeds the threshold, the observed value is considered abnormal, and robust filtering is used, whereby the impact of UWB data exceptions on the positioning results is reduced by exploiting Mahalanobis distance. Experimental results show that the observation error can be effectively estimated, and the proposed algorithm can achieve an improved positioning accuracy when affected by outlying system states of different quantity as well as outlying observations of different proportion.

scholarly journals Inertial measurement unit-based pose estimation: Analyzing and reducing sensitivity to sensor placement and body measures

2019 ◽  
Vol 6 ◽  
pp. 205566831881345 ◽  
Author(s):  
Rezvan Kianifar ◽  
Vladimir Joukov ◽  
Alexander Lee ◽  
Sachin Raina ◽  
Dana Kulić
Keyword(s):  
Pose Estimation ◽  
Inertial Measurement Unit ◽  
Kinematic Model ◽  
Sensor Placement ◽  
Estimation Method ◽  
Calibration Procedure ◽  
The Body ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Inertial Measurement

Introduction Inertial measurement units have been proposed for automated pose estimation and exercise monitoring in clinical settings. However, many existing methods assume an extensive calibration procedure, which may not be realizable in clinical practice. In this study, an inertial measurement unit-based pose estimation method using extended Kalman filter and kinematic chain modeling is adapted for lower body pose estimation during clinical mobility tests such as the single leg squat, and the sensitivity to parameter calibration is investigated. Methods The sensitivity of pose estimation accuracy to each of the kinematic model and sensor placement parameters was analyzed. Sensitivity analysis results suggested that accurate extraction of inertial measurement unit orientation on the body is a key factor in improving the accuracy. Hence, a simple calibration protocol was proposed to reach a better approximation for inertial measurement unit orientation. Results After applying the protocol, the ankle, knee, and hip joint angle errors improved to [Formula: see text], and [Formula: see text], without the need for any other calibration. Conclusions Only a small subset of kinematic and sensor parameters contribute significantly to pose estimation accuracy when using body worn inertial sensors. A simple calibration procedure identifying the inertial measurement unit orientation on the body can provide good pose estimation performance.

scholarly journals Pedestrian Tracking Solution Combining an Impulse Radio Handset Transmitter with an Ankle-Mounted Inertial Measurement Unit

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Joe Youssef ◽  
Benoît Denis ◽  
Christelle Godin ◽  
Suzanne Lesecq
Keyword(s):  
Inertial Measurement Unit ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Impulse Radio ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Time Of Arrival ◽  
Inertial Measurement ◽  
Loosely Coupled ◽  
Data Control

We address the indoor tracking problem by combining an Impulse Radio-Ultra-Wideband handset with an ankle-mounted Inertial Measurement Unit embedding an accelerometer and a gyroscope. The latter unit makes possible the detection of the stance phases to overcome velocity drifts. Regarding radiolocation, a time-of-arrival estimator adapted to energy-based receivers is applied to mitigate the effects of dense multipath profiles. A novel quality factor associated with this estimator is also provided as a function of the received signal-to-noise ratio, enabling us to identify outliers corresponding to obstructed radio links and to scale the covariance matrix of radiolocation measurements. Finally, both radio and inertial subsystems are loosely-coupled into one single navigation solution relying on a specific extended Kalman filter. In the proposed fusion strategy, processed inertial data control the filter state prediction whereas Combined Time Differences Of Arrival are formed as input observations. These combinations offer low computational complexity as well as a unique filter structure over time, even after removing outliers. Experimental results obtained in a representatively harsh indoor environment emphasize the complementarity of the two technologies and the relevance of the chosen fusion method while operating with low-cost, noncollocated, asynchronous, and heterogeneous sensors.

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