Accurate Attitude Estimation of a Moving Land Vehicle Using Low-Cost MEMS IMU Sensors

Ahmed, H.; Tahir, Muhammad

doi:10.1109/tits.2016.2627536

Cited by 137 publications

(98 citation statements)

References 34 publications

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“…Like Rogne et al [9], Ahmed and Tahir [20] recognize that high-performance IMU units contribute significantly to the overall system cost. That motivated the use of a low-cost Micro Electro-Mechanical System IMU unit, containing a triaxial gyroscope and accelerometer, to accurately determine the attitude of a car.…”

Section: Related Workmentioning

confidence: 97%

Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network

Skulstad

Fossen

et al. 2019

IEEE Robot. Automat. Mag.

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When a ship experiences a loss of position reference systems, the ship's navigation system typically enters a mode known as dead reckoning to maintain an estimate of the position of the ship. Commercial systems perform this task using a state estimator that includes mathematical model knowledge. Such a model is non-trivial to derive and needs tuning if the dynamic properties of the vessel change. To this end we propose to use machine learning to estimate the horizontal velocity of the vessel without the help of position, velocity or acceleration sensors. A simulation study was conducted to show the ability to maintain position estimates during a Global Navigation Satellite System outage. Comparable performance is seen relative to the established Kalman Filter model-based approach.

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Section: Related Workmentioning

confidence: 97%

Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network

Skulstad

Fossen

et al. 2019

IEEE Robot. Automat. Mag.

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“…Attitude measurement errors are easily produced due to gyro drift. The longer work time, the greater the error [15]. To solve this problem, a gyro drift compensation method is applied to increase the accuracy of attitude estimation.…”

Section: Accelerometer Compensation Strategymentioning

confidence: 99%

Accelerometer-Based Gyroscope Drift Compensation Approach in a Dual-Axial Stabilization Platform

Gao

Meng

et al. 2019

Electronics

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An accelerometer-based gyro drift compensation approach in a dual-axial stabilization platform is introduced in this paper. The stabilization platform consists of platform framework, drive motor, gyro and accelerometer module and contorl board. Gyro is an angular rate detecting element to achieve angular rate and rotation angle of the dynamic platform system. However, the platform system has an unstable factor because of the drift of gyro. The main contribution of this paper is to implement a convenient gyro drift compensation approach by using the accelerometer. In contrast to a kalman filtering method, this approach is simpler and practical due to the high-precision characteristic of the accelerometer. Data filtering algorithm and limit of threshold setting of total acceleration values are applied in this approach. The validity and feasibility of the proposed approach are evaluated by four tests under various conditions.

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“…A serial port was used to connect with the remote control to record the signal of driving and steering, which was used as the input of the simulation model. An LMS SCADAS ( 1 , SCM05) was used to record the data during the field test, and the sampling frequency was set as 100 Hz [23]. Two inertial measurement units (IMUs) ( 2 , 3 , SC-AHRS-200A) were installed in the front and rear frames, respectively.…”

Section: Field Test Setupmentioning

confidence: 99%

Hybrid Model-Based Analysis of Underground Articulated Vehicles Steering Characteristics

et al. 2019

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Owing to the harsh environment of underground mines, autonomous underground articulated vehicles (UAVs) with precise control and positioning system are particularly important. However, the ambiguity of steering characteristics hinders the development of UAVs. This study presents a model-based method to uncover the steering characteristics of a UAV. Firstly, a hybrid model of UAV was established, which included a dynamic model of articulated frames and a model of the hydraulic power steering system. Secondly, a field test of a typical UAV, a load-haul-dump (LHD) with 4 m3 capacity, was carried out. In order to verify the correctness of the established model and the accuracy of the involved parameters, the field test results were used to verify the dynamic model in time and frequency domains. Then, the steering characteristics of the UAV were uncovered based on the verified hybrid model, and the results showed that the increased load would increase ‘oversteering’ under the same articulation angle and that the error of trajectory exceeded 0.3 m. In addition, the deviations of trajectories between the two frames were revealed during the transient steering process, and the maximum deviation reached 0.21 m when the velocity was 2 m/s and the articulation angle was 15°. The comprehensive results indicate that the steering characteristics of UAVs cannot be ignored in regard to precise autonomous control and positioning.

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Accurate Attitude Estimation of a Moving Land Vehicle Using Low-Cost MEMS IMU Sensors

Cited by 137 publications

References 34 publications

Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network

Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network

Accelerometer-Based Gyroscope Drift Compensation Approach in a Dual-Axial Stabilization Platform

Hybrid Model-Based Analysis of Underground Articulated Vehicles Steering Characteristics

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