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Accurate and consistent ego motion estimation is a critical component of autonomous navigation. For this task, the combination of visual and inertial sensors is an inexpensive, compact, and complementary hardware suite that can be used on many types of vehicles. In this work, we compare two modern approaches to ego motion estimation: the Multi-State Constraint Kalman Filter (MSCKF) and the Sliding...
This paper presents the state-space modeling and control of a coupled-tank liquid level system. Observed-state feedback controller via eigenvalue assignment and LQG control are designed in discrete-time and implemented by an industrial controller PLC. Both control design methods are augmented with integral action for a reference tracking without steady-state error for step inputs. The aim of the study...
In this paper, a particle filtering algorithm is proposed for the challenging problem of multiple target tracking in ultra-wideband (UWB) radar sensor networks. The particle weights are derived analytically for the case of one transmitter and several receivers. The performance of the proposed particle algorithm is then evaluated through numerical results with comparison to the well-known Kalman filter...
Radio-based positioning methods are generally based on a separation of timescales, where each position update assumes the availability of synchronous measurements. This approach is convenient in the design of positioning algorithms, but fails to account for outdated information. We describe three distinct ways how the separation of timescales can adversely impact the design and execution of positioning...
The “inverted pendulum — cart” system, consisting of object and two regulators, is described by the discrete equations in the state space. The case when unknown parameters are in the state matrix and the management matrix is considered. The calculation technique of Fischer in-formation matrix in the steady state is used for the object parameters specification. The offered approach is actual and useful...
Motivated by the need to secure cyber-physical systems against attacks, we consider the problem of estimating the state of a noisy linear dynamical system when a subset of sensors is arbitrarily corrupted by an adversary. We propose a secure state estimation algorithm and derive (optimal) bounds on the achievable state estimation error. In addition, as a result of independent interest, we give a coding...
Hydraulic systems are one of the most common power source in both transport systems (i.e. aircrafts) and industrial systems. Electro hydraulic servovalves are critical components and often subjected to failures. This article presents a method to estimate degradation in a servovalve using an application of the Fading Extended Kalman Filter for system identification. A single failure mode related to...
Motor vehicle collisions are the leading cause of death in the Unites States. Rear-end crashes alone occur approximately 1.6 million times each year [1]. These statistics demonstrate the obvious need to reduce the number of vehicle collisions and save lives. In response, the government, automobile industry, and academia have conducted intensive research in an effort to enhance the safety in the U...
Distributed processing is a new paradigm to analyse the huge volume of video data in camera networks. This paper addresses the problem of distributed single target tracking considering false positives and missed detections. Target tracking is modelled as a dynamic state estimation problem with nonlinear process and measurement model. We propose to use the sigma point information filters combined with...
For a team of mobile robots with limited onboard resources, we propose a partially decentralized implementation of an extended Kalman filter for cooperative localization. In the proposed algorithm, unlike a fully centralized scheme that requires, at each timestep, information from the entire team to be gathered together and be processed by a single device, we only require that the robots communicate...
This paper presents a low-cost wearable fitness monitoring device utilizing a 6-axis Inertial Measurement Unit (IMU) embedding 3-axis gyroscope and 3-axis accelerometer. The objective is to measure the angular value form by the feet with respect to the gravitational vector while walking in order to estimate the stride length. Kalman filter is employed for the sensor fusion technique and data conditioning.
Atrial fibrillation (Afib), the most common type of cardiac arrhythmia, arises from abnormal electrical activity of atrial membrane. Electrophysiological dynamics of human atrial tissue is represented by biophysically detailed models. Such models are really complex and hard to use for analysis purposes such as parameter estimation based on patient data. Hence, there is a need for simpler yet biophysically...
In this paper, we propose a prediction model for breathing pattern based on observations from CBCT raw projection images. From the raw CBCT projections the diaphragm apex position is measured, which in turn is used for the state estimation. We use a novel state space model followed by an Unscented Kalman Filter (UKF). Our method is compared with one of the successful models called Local Circular Motion...
The Anti-lock braking system has been a subject of constant research since its inception. Numerous control strategies have been developed for the same but the effect of measurement noise on the system is often neglected. This paper aims to discuss use of an Extended Kalman Filter for sensor noise elimination. Conventional control strategies in conjunction with this filtering technique are used to...
This paper presents a comparative analysis of well-known state estimation methods that are commonly used in real systems. The aim of this research is to measure and then evaluate the robustness (i.e., a measure of performance when a small and deliberate changes are made to the method conditions) of these methods against modeling uncertainties. The state estimation methods include the Kalman Filter,...
Reverberated speech signals in noisy acoustical environments cause some problems such as reducing speech intelligibility, distinguishing speakers, locating source, quality for hands-free telephony, hearing aid, etc. Adaptive filters can be applied to suppress the interfering signals and reduce the reverberation effects or to dereverberate the received speech signals at microphone. In this paper, Bayesian...
In the control system consisting of object and regulators with it is inexact parameters, requires to estimate the parameters values by means of active identification method. The object is described by the linearized continuous and discrete equations. The external signals are planned. The determinant of the Fischer information matrix is calculated. The maximum value of determinant is reached by the...
This paper presents a novel robust method of self-corrective Initial Alignment of a stationary SINS1 with respect to local-level frame (NED-frame) depending only on the output of a strap-down IMU2. The proposed method provides a superior performance compared to traditionally-known self-corrective initial alignment methods. The main contribution of this paper is the development of a new algorithm which...
An unmanned small aircraft is expected to be applied to various applications, such as aerial photography, information gathering of disaster, transport of luggage, and inspection of infrastructure, such as bridges and tunnels. It needs to control the position of the Quadrotor, if it is used for the inspection of infrastructures, such as bridges etc. Therefore, we propose a method for controlling a...
It has always been difficult to accurately estimate the moment of inertia of an object, e.g. an unmanned aerial vehicle (UAV). Whilst various offline estimation methods exist to allow accurate parametric estimation by minimizing an error cost function, they require large memory consumption, high computational effort, and a long convergence time. The initial estimate's accuracy is also vital in attaining...
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