A Novel Fault-Tolerant Navigation and Positioning Method with Stereo-Camera/Micro Electro Mechanical Systems Inertial Measurement Unit (MEMS-IMU) in Hostile Environment

Cheng, Yuan; Lai, Jizhou; Lyu, Pin; Shi, Peng; Zhao, Wei; Huang, Kai

doi:10.3390/mi9120626

Cited by 13 publications

(9 citation statements)

References 22 publications

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“…But the most common accelerometers used in mobile application are classified as micro-electro-mechanical systems (MEMS) [39]. Therefore, progress in application of accelerometers in cars monitoring is correlated with microelectronics technology development [40] as well as with data processing and sensors integration for working in hostile environments [41]. It should be noted that some commercial companies offer small-dimension units that integrate accelerometers supported with wireless transmission to a remote unit, as for example the iNode Care Sensor family.…”

Section: Accelerometers and Their Application In Car Monitoringmentioning

confidence: 99%

Application of Wireless Accelerometer Mounted on Wheel Rim for Parked Car Monitoring

Borecki

Rychlik

Olejnik

et al. 2020

Sensors

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Damages of different kinds that can be inflicted to a parked car. Among them, loosening of the car wheel bolts is difficult to detect during normal use of the car and is at the same time very dangerous to the health and life of the driver. Moreover, in patents and publications, only little information is presented about electronic sensors available for activation from inside of the car to inform the driver about the mentioned dangerous situation. Thus, the main aim of this work is the proposition and examination of a sensing device using of a wireless accelerometer head to detect loosening of wheel fixing bolts before ride has been started. The proposed sensing device consists of a wireless accelerometer head, an assembly interface and a receiver unit. The assembly interface between the head and the inner part of the rim enables the correct operation of the system. The data processing algorithm developed for the receiver unit enables the proper detection of the unscrewing of bolts. Moreover, the tested algorithm is resistant to the interference signals generated in the accelerometer head by cars and men passing in close distance.

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Section: Accelerometers and Their Application In Car Monitoringmentioning

confidence: 99%

Application of Wireless Accelerometer Mounted on Wheel Rim for Parked Car Monitoring

Borecki

Rychlik

Olejnik

et al. 2020

Sensors

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“…This results in the odometer speed needing to be repeatedly integrated, which comes at the cost of increased computational complexity. To solve this problem, preintegration theory (Forster et al., 2017; Yuan et al., 2018) was introduced into the odometer. He et al.…”

Section: Introductionmentioning

confidence: 99%

Graph-optimisation-based self-calibration method for IMU/odometer using preintegration theory

et al. 2022

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Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.

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“…The environment is captured by the camera, then the relative motion between the camera and the environment is estimated. However, the estimation accuracy is usually affected by light interference [4]. In some dark and enclosed environments, such as caves and tunnels [5], a LIDAR-based navigation method is usually adopted.…”

Section: Introductionmentioning

confidence: 99%

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

Lyu

Wang

Lai

et al. 2019

Sensors

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In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.

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A Novel Fault-Tolerant Navigation and Positioning Method with Stereo-Camera/Micro Electro Mechanical Systems Inertial Measurement Unit (MEMS-IMU) in Hostile Environment

Cited by 13 publications

References 22 publications

Application of Wireless Accelerometer Mounted on Wheel Rim for Parked Car Monitoring

Application of Wireless Accelerometer Mounted on Wheel Rim for Parked Car Monitoring

Graph-optimisation-based self-calibration method for IMU/odometer using preintegration theory

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors

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