We benchmark in this article three different parametrizations for punctual landmarks in monocular 6DOF EKF-SLAM. These parametrizations are homogeneous points (HM), inverse-distance points (IDP, better known as inversedepth), and the new anchored homogeneous points (AHP). The discourse used for describing them is chosen to highlight their differences and similarities, showing that they are just...

In this paper, a novel algorithm to know the pose of any autonomous vehicle is described. Such a system (Attitude and Heading Reference System, AHRS) is essential for real time vehicle navigation, guidance and control applications. For low funded projects, with simple sensors, efficient and robust algorithms become necessary for an acceptable performance, and the well-known extended Kalman filt...

I n the control of batch distillation columns, one of the problems is the difficulty in monitoring the compositions. This problem can be handled by estimating the compositions from readily available online temperature measurements using a state estimator. In this study, a state estimator that infers the product composition in a multicomponent batch distillation column (MBDC) from the temperatur...

In this work, we study the inconsistency 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 system. A...

This paper describes a geometrically constrained Extended Kalman Filter (EKF) framework for a line feature based SLAM, which is applicable to a rectangular indoor environment. Its focus is on how to handle sparse and noisy sensor data, such as PSD infrared sensors with limited range and limited number, in order to develop a low-cost navigation system. It has been applied to a vacuum cleaning ro...

In this paper, we present an Extended Kalman Filter (EKF)-based estimator for simultaneous localization and mapping (SLAM) with processing requirements that are linear in the number of features in the map. The proposed algorithm, called the Power SLAM, is based on three key ideas. Firstly, by introducing the Global Map Postponement method, approximations necessary for ensuring linear computatio...

Some signals, such as in radar systems, communication systems, and neural systems, are transmitted as periodic pulse trains. If more than one pulse train is transmitted over the same communication channel, a challenge is to separate them for source identification at the receiver. This is known as pulse train deinterleaving and is clearly a fundamental problem in the study of discrete-event syst...

Department of Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan Contact: : [email protected] [email protected] [email protected] ABSTRACT: This paper presents the sensor-less control of a PMSM using extended Kalman Filter and a four switch three phase inverter implemented using FPGA Spartan 3-e. The system was modeled in Matlab/Simulink® and ver...

This paper deals with the problem of mobile-robot localization in structured environments. The extended Kalman filter (EKF) is used to localize the fourwheeled mobile robot equipped with encoders for the wheels and a laser-rangefinder (LRF) sensor. The LRF is used to scan the environment, which is described with line segments. A prediction step is performed by simulating the kinematic model of ...

In the present paper, we consider the problem of parameter estimation of wideband polynomial phase signals (PPS) impinging on a uniform linear array antenna. The parameters of interest are the polynomial phase coefficients and the direction of arrival of the signal. The principle of estimation is based on the introduction of an exact but unfortunately nonlinear state space modelization, of the ...