Gregorio Vettori

Cooperative localization of a team of AUVs by a tetrahedral configuration

This paper investigates the principles of a Cooperative Localization Algorithm for a team of at least three Autonomous Underwater Vehicles (AUVs) with respect to a surface support ship, without the use of Ultra-Short Baseline (USBL). It is assumed that each AUV is equipped with a low-cost Inertial Measurement Unit (IMU), a compass and a depth sensor, but only one of them has a high accuracy navigation sensor such as the Doppler Velocity Log (DVL). The surface boat locates itself by means of Global Positioning System (GPS). Range measurements provided by acoustic modems allow to avoid an unbounded error growth in the position estimate of each AUV. A geometric method, based on a tetrahedral configuration to obtain a deterministic fix for position, is proposed. This method allows to extend the advantages of the use of the DVL to the position estimate of other vehicles not equipped with DVL. The paper addresses also some of the problems related to the limitations of acoustic communication. The algorithm has been implemented and tested in simulations for a fleet of three AUVs and a surface support ship. An innovative cooperative localization algorithm for AUVs has been designed.Acoustic modems for communication are used as sensors of relative distance.The method is based on geometric relationships of a tetrahedral configuration.The algorithm performance are tested through a complete simulation model.A periodic reset of the estimation error is obtained for all the AUVs of the team.

Evaluation of odometry algorithm performances using a railway vehicle dynamic model

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances.

Localization algorithm for a fleet of three AUVs by INS, DVL and range measurements

The strong research efforts undergone in Marine Robotics during the last two decades open great possibilities for maritime operations. Autonomous Underwater Vehicles (AUVs) take the crew away from dangerous situations at depths of sea, with available and cost-affordable technology. MDM Lab, the Laboratory of Mechatronics and Dynamic Modelling of the University of Florence, is partner of the Thesaurus project, funded by Regione Toscana, with the aim of designing a moderate-cost AUV, called Tifone, to be used, in swarm, for research and monitoring of archaeological sites. In this paper we propose a Localization Algorithm for a fleet of three vehicles and a surface support ship which employs several sensors. Each AUV is equipped with low-cost sensors such as IMU, magnetometer and depth sensor; two of them have an high accuracy velocity sensor such as the Doppler Velocity Log. Acoustic modems, used for communication between AUVs, can provide the time of flight from an AUV to an another one. The positions estimated with a Range-Based algorithm fuse with the ones estimated by INS&DVL, avoiding unbounded error growth in the position estimate of the AUVs.

A localization algorithm for railway vehicles based on sensor fusion between tachometers and inertial measurement units

The availability of a reliable speed and travelled distance estimation is relevant for the efficiency and safety of automatic train protection and control systems. This paper investigates the main features of an innovative localization algorithm that integrates tachometers and inertial measurement units. Nowadays, the estimation is performed by an odometry algorithm that relies on wheel angular speed sensors. The objective is to increase the accuracy of the odometric estimation, especially in critical adhesion conditions, through sensor fusion techniques based on Kalman filter theory. The Italian company ECM S.p.A. has supported the project, providing a custom inertial measurement unit based on micro electro-mechanical system sensors for the on-track testing of the algorithm. The preliminary results show a significant improvement of the position and speed estimation performances compared to those obtained with SCMT (Italian acronym for ‘Sistema Controllo Marcia Treno’) algorithms, currently in use on the Italian railway network. A wide set of simulated test results, showing the improvement of the estimation process, is presented and discussed. An accurate train navigation that scarcely relies on information from the infrastructure will open a road map for the development of a more and more effective and efficient exploitation of the railway infrastructure.

A localization algorithm for railway vehicles

Odometry is a safety on-board subsystem of modern railway Automatic Train Protection (ATP) and Automatic Train Control (ATC) and his main task is the estimation of instantaneous speed and the travelled distance of the railway vehicle. An accurate estimation is mandatory, because an error (residual) on the train position may lead to a dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, the proposed algorithm exploits data fusion of different inputs coming from a redundant sensor layout: in particular, the proposed strategy consists of a sensor fusion between the information coming from a tachometer and an IMU (Inertial Measurements Unit) is carried out. A 3D multibody model has been designed so at to simulate the sensor outputs. Within the framework of the presented research, a custom IMU, designed by ECM S.p.a. has been built. The IMU board is then tested via a dedicated HIL test rig (Hardware in the Loop) that includes an industrial robot able to reproduce the motion of the railway vehicle. The performances of the innovative localization algorithm have been evaluated by generating the experimental outputs. The main aim of this work is the development of an innovative localization algorithm for railway vehicles able to enhance the speed and position estimation accuracy of the classical odometry algorithms, such as the Italian SCMT (Sistema Controllo Marcia Treno). The results highlight a good improvement of the position and speed estimation performances compared to those obtained with classical SCMT algorithms, currently in use on the Italian railway network.

Design and implementation of dynamic simulators for the testing of inertial sensors

Many dynamic simulators have been developed in the last thirty years for different types of vehicles. Flight simulators and drive simulators are very well known examples. This paper describes the design and implementation of a dynamic simulator for the testing of inertial sensors devoted to vehicle navigation through a Hardware-In-The-Loop test rig composed of an industrial robot and a commercially available Inertial Measurement Unit (IMU). The authors are developing an innovative localization algorithm for railway vehicles which integrates inertial sensors with tachometers. The opportunity to set up a testing simulator capable of replicating in a realistic fashion the dynamic effects of the vehicle motion on inertial sensors allows to avoid expensive on board acquisitions and to speed up algorithm tuning. The real-time control architecture featured by the available industrial robot allows to precisely specify and execute motion trajectories with tight path and time law constraints required by the application at hand.

An innovative localisation algorithm for railway vehicles

In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements. The estimation strategy has good performance also under degraded adhesion conditions and could be put on board of high-speed railway vehicles; it represents an accurate and reliable solution. The IMU board is tested via a dedicated Hardware in the Loop (HIL) test rig: it includes an industrial robot able to replicate the motion of the railway vehicle. Through the generated experimental outputs the performances of the innovative localisation algorithm have been evaluated: the HIL test rig permitted to test the proposed algorithm, avoiding expensive (in terms of time and cost) on-track tests, obtaining encouraging results. In fact, the preliminary results show a significant improvement of the position and speed estimation performances compared to those obtained with SCMT algorithms, currently in use on the Italian railway network.