Additive Gaussian noise model and Kalman filter to enhance controllability of gesture-controlled teleoperated soft actuators

2020 ◽  
pp. 095440542094100
Author(s):  
PDSH Gunawardane ◽  
APTD Pathirana ◽  
REA Pallewela ◽  
Nimali T Medagedara
Keyword(s):  
Kalman Filter ◽  
Gaussian Noise ◽  
Noise Model ◽  
The Internet ◽  
Linear Calibration ◽  
Spherical Object ◽  
Gesture Control ◽  
Soft Actuators ◽  
Human Finger ◽  
And Control

Soft actuators are used in bilateral systems as slave-side actuators. To broaden the applications and usage of these soft actuators in teleoperated applications required high accuracy and control. This article focuses on the improvement and control of the soft actuators operated through the Internet using a glove-based gesture control system. A hand-worn sensor glove (a glove with flex sensors and accelerometers) is used to detect hand gestures (specifically bending angle and force generated in a finger while gripping a spherical object) of an operator. The operator’s finger movements are mimicked in a remote location, through the Internet, in a soft actuator. The bending angles of the human finger have converted into the pressure variations inside the actuator using a linear calibration technique. A vertically mounted actuator and a spherical object are used to demonstrate the gripping action. The main problems that occurred during the controlling of this setup are noise and delays. Electronic noise (line noise and circuit noise), mechanical noise (vibration, nonuniformities in actuator fabrication, wear, and tear), elastic effect (energy absorbed during the state transformation), communication delays (delays occurred due to geography, telecommunication infrastructure, and round trip transmission), and other noises (other environmental effects) degraded the performance. This article considered a Brownian motion model, an additive Gaussian noise model, and a Kalman filter to solve these problems. The experimentations are performed in three different locations (to demonstrate the teleoperation) and the recorded improvement in the performance is approximately 17%.

Update of the last 2 years on the impact of the internet and social networks on the management of type 2 diabetes mellitus: simple review. (Preprint)

2020 ◽  
Author(s):  
Mayli Lañas-Navarro ◽  
Jose Ipanaque-Calderon Sr ◽  
Fiorela E Solano
Keyword(s):  
Social Networks ◽  
Mobile Applications ◽  
Health Personnel ◽  
Online Courses ◽  
The Internet ◽  
Diabetic Patients ◽  
Bibliographic Search ◽  
Use Of The Internet ◽  
And Control ◽  
The Impact

BACKGROUND Research on the use of the Internet in the medical field is experiencing many advances, including mobile applications, social networks, telemedicine. Its implementation in medical care and comprehensive patient management is a much discussed topic at present. OBJECTIVE This narrative review aims to understand the impact of the internet and social networks on the management of diabetes, both for patients and medical staff. METHODS The bibliographic search was carried out in the databases Pubmed, Virtual Health Library (VHL) and Lilacs between 2018 to 2020. RESULTS Multiple mobile applications have been created for the help and control of diabetic patients, as well as the implementation of online courses, improving the knowledge of health personnel applying them in the field of telemedicine. CONCLUSIONS The use of the Internet and social networks brings many benefits for both the diabetic patient and the health personnel, offering advantages for both.

Centered error entropy Kalman filter with application to satellite attitude determination

2021 ◽  
pp. 014233122110198
Author(s):  
Baojian Yang ◽  
Lu Cao ◽  
Dechao Ran ◽  
Bing Xiao
Keyword(s):  
Kalman Filter ◽  
Gaussian Noise ◽  
Attitude Determination ◽  
Complexity Analysis ◽  
Iteration Algorithm ◽  
Robust Algorithms ◽  
Convergence Conditions ◽  
Satellite Attitude ◽  
Heavy Tailed ◽  
Non Gaussian

Due to unavoidable factors, heavy-tailed noise appears in satellite attitude estimation. Traditional Kalman filter is prone to performance degradation and even filtering divergence when facing non-Gaussian noise. The existing robust algorithms have limited accuracy. To improve the attitude determination accuracy under non-Gaussian noise, we use the centered error entropy (CEE) criterion to derive a new filter named centered error entropy Kalman filter (CEEKF). CEEKF is formed by maximizing the CEE cost function. In the CEEKF algorithm, the prior state values are transmitted the same as the classical Kalman filter, and the posterior states are calculated by the fixed-point iteration method. The CEE EKF (CEE-EKF) algorithm is also derived to improve filtering accuracy in the case of the nonlinear system. We also give the convergence conditions of the iteration algorithm and the computational complexity analysis of CEEKF. The results of the two simulation examples validate the robustness of the algorithm we presented.

scholarly journals Revisiting the nonlinear Gaussian noise model for hybrid fiber spans

2021 ◽  
Vol 2 (1) ◽  
pp. 30-49
Author(s):  
Ioannis Roudas ◽  
Jaroslaw Kwapisz ◽  
Xin Jiang
Keyword(s):  
Gaussian Noise ◽  
Noise Model ◽  
Hybrid Fiber

Image Denoising via Bayesian Estimation of Statistical Parameter Using Generalized Gamma Density Prior in Gaussian Noise Model

2015 ◽  
Vol 14 (02) ◽  
pp. 1550017
Author(s):  
Pichid Kittisuwan
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Gaussian Noise ◽  
Classical Problem ◽  
Statistical Parameter ◽  
Noise Model ◽  
Natural Image ◽  
Bayesian Techniques ◽  
Generalized Gamma ◽  
Gamma Density

The application of image processing in industry has shown remarkable success over the last decade, for example, in security and telecommunication systems. The denoising of natural image corrupted by Gaussian noise is a classical problem in image processing. So, image denoising is an indispensable step during image processing. This paper is concerned with dual-tree complex wavelet-based image denoising using Bayesian techniques. One of the cruxes of the Bayesian image denoising algorithms is to estimate the statistical parameter of the image. Here, we employ maximum a posteriori (MAP) estimation to calculate local observed variance with generalized Gamma density prior for local observed variance and Laplacian or Gaussian distribution for noisy wavelet coefficients. Evidently, our selection of prior distribution is motivated by efficient and flexible properties of generalized Gamma density. The experimental results show that the proposed method yields good denoising results.

Maximum Correntropy Criterion Constrained Kalman Filter

2017 ◽  
Author(s):  
Seyed Fakoorian ◽  
Mahmoud Moosavi ◽  
Reza Izanloo ◽  
Vahid Azimi ◽  
Dan Simon
Keyword(s):  
Kalman Filter ◽  
Gaussian Noise ◽  
State Constraints ◽  
Statistical Information ◽  
Second Order ◽  
System Model ◽  
Error Covariance ◽  
Inequality State ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian

Non-Gaussian noise may degrade the performance of the Kalman filter because the Kalman filter uses only second-order statistical information, so it is not optimal in non-Gaussian noise environments. Also, many systems include equality or inequality state constraints that are not directly included in the system model, and thus are not incorporated in the Kalman filter. To address these combined issues, we propose a robust Kalman-type filter in the presence of non-Gaussian noise that uses information from state constraints. The proposed filter, called the maximum correntropy criterion constrained Kalman filter (MCC-CKF), uses a correntropy metric to quantify not only second-order information but also higher-order moments of the non-Gaussian process and measurement noise, and also enforces constraints on the state estimates. We analytically prove that our newly derived MCC-CKF is an unbiased estimator and has a smaller error covariance than the standard Kalman filter under certain conditions. Simulation results show the superiority of the MCC-CKF compared with other estimators when the system measurement is disturbed by non-Gaussian noise and when the states are constrained.

Analysis of the Slovak Discourses of Sex Education Inspired by Michel Foucault

Human Affairs ◽  
2010 ◽  
Vol 20 (1) ◽  
Author(s):  
Ivan Lukšík ◽  
Dagmar Marková
Keyword(s):  
Young People ◽  
Religious Education ◽  
Sex Education ◽  
Michel Foucault ◽  
The Internet ◽  
Children And Young People ◽  
Basic Ability ◽  
And Control

Analysis of the Slovak Discourses of Sex Education Inspired by Michel FoucaultThe aims, rules and topics of sex education exist on paper, but have yet to be implemented in Slovakia. Although the curriculum creates the illusion of openness in this field, the silence on sex education in schools provides space for the alternative, "more valuable" quiet discourses of religious education. Under these conditions, it is silence that is proving to be an advantageous strategy for the majority of those who should be voicing their opinions. Instead, they listen and control. By contrast, those who do speak out, children and young people, do not in fact, speak to them, but mainly among themselves. Those who are silent and listen are not prepared for the younger generations confessions on sexuality, which are mostly taken from the liberal area of media, especially the internet. The silent frequently lack, at the very least, the basic ability to react and debate in this changed situation. Those who are involved in the discussion on sexuality in Slovakia are those who should listen and supervise.

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