Review and selection of commercially available IMU for a short time inertial navigation

Borodacz, Krystian; Szczepański, Cezary; Popowski, S.

doi:10.1108/aeat-12-2020-0308

Cited by 15 publications

(19 citation statements)

References 4 publications

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“…In both cases, the results obtained will be compared with the common approach, which considers only time-dependent errors. The analysis considers the measurement system errors listed in Table 3 with values taken from the documentation of a selected tactical grade IMU available on the market [ 1 ].…”

Section: Resultsmentioning

confidence: 99%

“…It should be noted that the listed parameters are typical for IMUs available on the market [ 1 ], which represent only a cross section of existing sensor technologies [ 17 ]. Therefore, it should be assumed that the models presented below based on these parameters are applicable to optical gyroscopes, i.e., ring laser gyroscope (RLG) or fibre optic gyroscope (FOG) and sensors manufactured with micro-electro-mechanical systems (MEMS) technology.…”

Section: Methodsmentioning

confidence: 99%

“…As a first step, an estimate of the required sensors’ accuracy can be determined based solely on navigation duration by considering the time-dependent errors due to sensor bias and random walk parameters [ 1 ]. A more detailed analysis, however, requires consideration of errors that build up during motion due to the predicted trajectory and sensors’ sensitivity to motion parameters.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

Borodacz

Szczepański

2023

Sensors

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The selection of an appropriate measurement system for an inertial navigation system requires an analysis of the impact of sensor errors on the position and orientation determination accuracy to ensure that the selected solution is cost-effective and complies with the requirements. In the current literature, this problem is solved based on the navigation duration only by considering the time-dependent errors due to sensor bias and random walk parameters or by conducting numerous simulations. In the former case, oversimplifying the analysis will not allow accurate values to be determined, while the latter method does not provide direct insight into the emerging dependencies. In contrast, this article introduces an analytic approach with a detailed model. This article presents general formulas, also written in detail for the measurement system model adopted and various manoeuvres. Although general equations are complicated, the use of piecewise constant motion variables allow us to discern fragments of equations corresponding to individual error sources. The results confirm the effect the carouseling has on the reduction of navigation errors. The general formulas presented extend the potential to analyse the influence of the entire host vehicle motion, while the detailed formulas make dependencies between motion and navigational errors evident.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

Borodacz

Szczepański

2023

Sensors

Self Cite

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“…This is also achievable with a low-cost IMU using Arduino [ 37 ]. For an in-depth review of modern inertial navigation systems and commercially available products, please refer to [ 24 , 38 ].…”

Section: Sensors and Sensor-based Odometry Methodsmentioning

confidence: 99%

Sensors and Sensor Fusion Methodologies for Indoor Odometry: A Review

et al. 2022

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Although Global Navigation Satellite Systems (GNSSs) generally provide adequate accuracy for outdoor localization, this is not the case for indoor environments, due to signal obstruction. Therefore, a self-contained localization scheme is beneficial under such circumstances. Modern sensors and algorithms endow moving robots with the capability to perceive their environment, and enable the deployment of novel localization schemes, such as odometry, or Simultaneous Localization and Mapping (SLAM). The former focuses on incremental localization, while the latter stores an interpretable map of the environment concurrently. In this context, this paper conducts a comprehensive review of sensor modalities, including Inertial Measurement Units (IMUs), Light Detection and Ranging (LiDAR), radio detection and ranging (radar), and cameras, as well as applications of polymers in these sensors, for indoor odometry. Furthermore, analysis and discussion of the algorithms and the fusion frameworks for pose estimation and odometry with these sensors are performed. Therefore, this paper straightens the pathway of indoor odometry from principle to application. Finally, some future prospects are discussed.

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“…A range of other IMU chips can be selected, as required [35]. (c) The battery is Li-Po type with a capacity of 240 mAh.…”

Section: Wsa Units Hardwarementioning

confidence: 99%

Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

Munih¹,

Ivanić²,

Kamnik³

2021

Applied Sciences

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We describe the Wearable Sensory Apparatus (WSA) System, which has been implemented and verified in accordance with the relevant standards. It comprises the Inertial Measurement Units (IMUs), real-time wireless data transmission over Ultrawideband (UWB), a Master Unit and several IMU dongles forming the Wireless Body Area Network (WBAN). The WSA is designed for, but is not restricted to, wearable robots. The paper focuses on the topology of the communication network, the WSA hardware, and the organization of the WSA firmware. The experimental evaluation of the WSA incorporates the confirmation of the timing using the supply current WSA profile, measurements related to determining the less error prone position of the master device on the backpack, measurements of the quality of the data transfer in a real environment scenario, measurements in the presence of other microwave signals, and an example of raw IMU signals during human walking. Placement of the master device on the top of the backpack was found to be less error prone, with less than 0.02% packet loss for all the IMU devices placed on different body segments. The packet loss did not change significantly in public buildings or on the street. There was no impact of Wi-Fi bands on the WSA data transfer. The WSA hardware and firmware passed conformance testing in a certified lab. Most importantly, the WSA performed reliably in the laboratory and in clinical tests with exoskeletons and prostheses.

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Review and selection of commercially available IMU for a short time inertial navigation

Cited by 15 publications

References 4 publications

Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

Sensors and Sensor Fusion Methodologies for Indoor Odometry: A Review

Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

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