This paper describes a hybrid approach to a fast and accurate localization method for legged robots based on Fuzzy-Markov (FM) and Extended Kalman Filters (EKF). Both FM and EKF techniques have been used in robot localization and exhibit different characteristics in terms of processing time, convergence, and accuracy. We propose a Fuzzy-Markov–Kalman (FM–EKF) localization method as a combined s...

Abstract: Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) is used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line).Tuning an EKF is the process of estimation of th...

This paper discusses a state space estimation for an electromechanical actuator valve using extended Kalman filter (EKF). A proposed actuator model includes a Tustin’s friction model with strong nonlinearities, hence it represents an accurate model for describing the friction phenomenon in an electromechanical actuator valve. At first the state equations of the model were converted into a time-...

In this work, we study the inconsistency problem of EKF-based SLAM from the perspective of observability. We analytically prove that when the Jacobians of the system and measurement models are evaluated at the latest state estimates during every time step, the linearized error-state system employed in the EKF has observable subspace of dimension higher than that of the actual, nonlinear, SLAM s...

This paper presents a detailed study of the extended Kalman filter (EKF) for estimating the rotor resistance and rotor speed of an induction motor drive. The overall structure of the EKF is reviewed and the various system vectors and matrices are defined. By including the rotor resistance and rotor speed as a state variables, the EKF equations are established from a discrete two-axis model of t...

The parameter estimation problem for polynomial phase signals (PPSs) arises in a number of fields, including radar, sonar, biology, etc. In this paper, a fast algorithm of parameter estimation for monocomponent PPS is considered. We propose the so-called LSU-EKF estimator, which combines the least squares unwrapping (LSU) estimator and the extended Kalman filter (EKF). First, the coarse estimat...

A robust extended Kalman filter (EKF) is proposed as a method for estimation of the state of charge (SOC) of lithium-ion batteries used in hybrid electric vehicles (HEVs). An equivalent circuit model of the battery, including its electromotive force (EMF) hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analy...

In this paper extended Kalman filter (EKF) is reviewed for estimating the rotor position/speed of a vector controlled five-phase induction motor drive. The basic configuration of the Kalman filter is studied and the system vectors and matrices are explained. The EKF equations are made from a d-q-axis model of the five-phase induction motor by considering the rotor speed as a state variable. The...

With the recent advance of deep learning based object recognition and estimation, it is possible to consider level SLAM where pose each estimated in process. In this letter, on a novel Lie group structure, right invariant extended Kalman filter (RI-EKF) for proposed. The observability analysis shows that proposed algorithm automatically maintains correct unobservable subspace, while standard EK...

This paper presents a comparison of different fitters namely: Extended Kalman Filter (EKF), Particle Filter (PF) and a proposed Enhanced Particle / Kalman Filter (EPKF) used in robot localization. These filters are implemented in matlab environment and their performances are evaluated in terms of computational time and error from ground truth and the results are reported. The considered robot l...