Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion

Guo, Hui; Hong, Huajie

doi:10.3390/s19163552

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…Kalman filtering can also be used to process gyroscope readings which are susceptible to noise and drift. The other technique to improve gyroscopic readings is to model the gyroscope random noise and then offsetting it according to the model, this is referred to as model compensation [ 71 ].…”

Section: Drone Hardware Overviewmentioning

confidence: 99%

A review on drones controlled in real-time

Kangunde

Jamisola

Theophilus

2021

Int. J. Dynam. Control

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This paper presents related literature review on drones or unmanned aerial vehicles that are controlled in real-time. Systems in real-time control create more deterministic response such that tasks are guaranteed to be completed within a specified time. This system characteristic is very much desirable for drones that are now required to perform more sophisticated tasks. The reviewed materials presented were chosen to highlight drones that are controlled in real time, and to include technologies used in different applications of drones. Progress has been made in the development of highly maneuverable drones for applications such as monitoring, aerial mapping, military combat, agriculture, etc. The control of such highly maneuverable vehicles presents challenges such as real-time response, workload management, and complex control. This paper endeavours to discuss real-time aspects of drones control as well as possible implementation of real-time flight control system to enhance drones performance.

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Section: Drone Hardware Overviewmentioning

confidence: 99%

A review on drones controlled in real-time

Kangunde

Jamisola

Theophilus

2021

Int. J. Dynam. Control

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“…In order to obtain more accurate data during the operation of the MPU6050 sensor we chose to filter the data using the Kalman filter. This filter not only can filter the signal coming from the gyroscope, but also can filter the signal coming from the accelerometer [ 32 ]. To filter the signal from the gyroscope and accelerometer we implemented a program with the Kalman algorithm on the microcontroller that takes data from these sensors, and to implement the Kalman algorithm we used the steps we described in implementing the EMG sensor algorithm.…”

Section: Software Application Developmentmentioning

confidence: 99%

Development of a Virtual Reality Simulator for an Intelligent Robotic System Used in Ankle Rehabilitation

Covaciu

Pîslă

Iordan

2021

Sensors

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The traditional systems used in the physiotherapy rehabilitation process are evolving towards more advanced systems that use virtual reality (VR) environments so that the patient in the rehabilitation process can perform various exercises in an interactive way, thus improving the patient’s motivation and reducing the therapist’s work. The paper presents a VR simulator for an intelligent robotic system of physiotherapeutic rehabilitation of the ankle of a person who has had a stroke. This simulator can interact with a real human subject by attaching a sensor that contains a gyroscope and accelerometer to identify the position and acceleration of foot movement on three axes. An electromyography (EMG) sensor is also attached to the patient’s leg muscles to measure muscle activity because a patient who is in a worse condition has weaker muscle activity. The data collected from the sensors are taken by an intelligent module that uses machine learning to create new levels of exercise and control of the robotic rehabilitation structure of the virtual environment. Starting from these objectives, the virtual reality simulator created will have a low dependence on the therapist, this being the main improvement over other simulators already created for this purpose.

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“…For example, the authors of [ 15 ] exploited a KF for accurate biases estimation in a distributed-tracking system, while the authors of [ 16 ] identified and successfully removed noise using a KF in a real-time application. In order to reduce the noise and compensate for the drift of the Micro Electro Mechanical Systems (MEMS) gyroscope during usage, the authors of [ 17 ] proposed a Kalman filtering method based on information fusion. In [ 18 ], the authors proposed an algorithm based on an external acceleration compensation model to be used as a modifying parameter in adjusting the measurement noise covariance matrix of the EKF.…”

Section: Related Workmentioning

confidence: 99%

DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation

Russo

Ciaccio

Troisi

2021

Sensors

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One of the main issues for the navigation of underwater robots consists in accurate vehicle positioning, which heavily depends on the orientation estimation phase. The systems employed to this end are affected by different noise typologies, mainly related to the sensors and to the irregular noise of the underwater environment. Filtering algorithms can reduce their effect if opportunely configured, but this process usually requires fine techniques and time. This paper presents DANAE++, an improved denoising autoencoder based on DANAE (deep Denoising AutoeNcoder for Attitude Estimation), which is able to recover Kalman Filter (KF) IMU/AHRS orientation estimations from any kind of noise, independently of its nature. This deep learning-based architecture already proved to be robust and reliable, but in its enhanced implementation significant improvements are obtained in terms of both results and performance. In fact, DANAE++is able to denoise the three angles describing the attitude at the same time, and that is verified also using the estimations provided by an extended KF. Further tests could make this method suitable for real-time applications in navigation tasks.

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Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion

Cited by 13 publications

References 11 publications

A review on drones controlled in real-time

A review on drones controlled in real-time

Development of a Virtual Reality Simulator for an Intelligent Robotic System Used in Ankle Rehabilitation

DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation

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