Leopoldo Jetto

Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots

A basic requirement for an autonomous mobile robot is its capability to elaborate the sensor measures to localize itself with respect to a coordinate system. To this purpose, the data provided by odometric and sonar sensors are here fused together by means of an extended Kalman filter. The performance of the filter is improved by an online adjustment of the input and measurement noise covariances obtained by a suitably defined estimation algorithm.

Approximation of the algebraic Riccati equation in the Hilbert space of Hilbert-Schmidt operators

This paper deals with the problem of approximating the infinite-dimensional algebraic Riccati equation, considered as an abstract equation in the Hilbert space of Hilbert–Schmidt operators. Two kin...

Localization of mobile robots: Development and comparative evaluation of algorithms based on odometric and inertial sensors

An autonomous mobile robot must be able to elaborate the measures provided by the sensor equipment to localize itself with respect to a coordinate system. The precision of the location estimate depends on the sensor accuracy and on the reliability of the measure processing algorithm. The purpose of this article is to propose a low cost positioning system using internal sensors like odometers and optical fiber gyroscopes. Three simple localization algorithms based on different sensor data processing procedures are presented. Two of them operate in a deterministic framework, the third operates in a stochastic framework where the uncertainty is induced by sensing and unmodeled robot dynamics. The performance of the proposed localization algorithms are tested through a wide set of laboratory experiments and compared in terms of localization accuracy and computational cost.

Efficient LMI-Based Quadratic Stabilization of Interval LPV Systems With Noisy Parameter Measures

The purpose of this note is to consider the quadratic stabilization of LPV systems in the realistic case where only Gaussian noisy parameter measures are available. Though neglected in the actual literature on LPV systems, this question is particular important because in all situations of a practical interest the parameter measurements (or estimates) are never exact. The assumed noisy nature of physical parameter readings requires a specifically developed approach consisting of mixed robust and LPV control methods. In the present case, an approach based on a vertex result on interval time varying (ITV) matrices is proposed. This allows the solvability conditions to be stated in terms of a set of LMIs, whose number is independent of the number of time-varying parameters.

Ripple-free dead-beat tracking for multirate sampled-data systems

In this paper, a solution is given to the problem of dead-beat ripple-free tracking for a multivariable multirate sampled-data system. The solution of such a problem is reduced to the solution of a dead-beat tracking problem for the corresponding discrete-time periodic system by introducing an additional requirement of dead-beat control for the control input of the multirate sampled-data system. The conditions for the problem solvability include the existence of a continuous-time internal model of all reference signals in the continuous-time plant. The design procedure of the periodic discrete-time compensator reduces to the design of a dead-beat periodic controller.

Improving the Robustness Properties of Robot Localization Procedures with Respect to Environment Features Uncertainties

In this paper the localization and environment feature estimation problems are formulated in a stochastic setting and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, gyroscope and sonar measures. As gyroscopic measures are much more reliable than the other ones, the localization algorithm gives rise to a nearly singular EKF. This problem is dealt with defining a lower order non singular EKF.

Robust stabilization of multivariable uncertain plants via switching control

In general, interval plants with a large uncertainty can not be robustly stabilized by a linear, time-invariant controller. The solution presented in this paper is in terms of an overall non linear control law given by the connection of a linear, deterministic, time-varying compensator and of a supervisor. The compensator may assume a finite number of possible different configurations, at least one of the which stabilizes the plant. The task of the supervisor is that of determining the switching instants of a scanning among the elements of the family, according to a suitably defined experimental test on the output of the system.

Space-variant recursive restoration of noisy images

A new approach to the modeling and filtering problems of nonhomogeneous images is proposed. The main assumption is that the whole image can be modeled by a collection of open subregions where the 2-D signal is regular enough to be well described by a smooth two-dimensional Gaussian process. The boundary points between two adjacent subregions are the image edges which represent sharp discontinuities in the signal distribution. A non-stationary state-space representation with structural information about image edges is then obtained. This allows the model to vary, adapting to the presence of spatial discontinuities. The reported simulation results show high filter performances. >

Ripple-free tracking problem

In the deadbeat control of discrete plants originating from continuous ones, it is important to have exact tracking, not only at the sampling instants, but also in between the instants. This paper investigates such a problem in the general case of a reference signal that can vary within a pre-specified class. The design procedure proposed here is based on a polynomial algebra approach. An internally stable closed-loop system is derived by means of an algorithm, where the transfer function of the controller originates from the solution of a set of linear equations. Algebraic conditions are given to determine the minimum time control scheme. Numerical examples are reported, to show the feasibility of the method and the simplicity of including other specific requirements into the control law.

Deadbeat ripple-free tracking with disturbance rejection: a polynomial approach

The deadbeat ripple-free tracking problem for sampled data systems is considered. It is assumed that both the state and the output of the continuous-time plant to be controlled are affected by external disturbances. A polynomial approach is adopted and solvability conditions are given both in terms of the sampled system and of the original continuous-time one. >