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Tech for care

April 8, 2020
tags:

“Tech For Care https://techforcare.com/ è una selezione di risorse, soluzioni, tecnologie, macchine intelligenti e robot per contrastare l’epidemia ed i suoi effetti – oggi e ovunque servano. I progetti sono accessibili e disponibili per tutti: gli operatori sanitari e quelli impegnati a produrre beni e servizi essenziali, e chiunque conosca reali bisogni di aiuto, potrà descrivere le necessità, cercare tra le soluzioni disponibili o collaborare a definire nuove soluzioni. Se sei un maker, uno sviluppatore, un’azienda, un ricercatore, un ingegnere delle macchine intelligenti, un esperto di robotica e vuoi contribuire, sottoponi il tuo progetto. Questa piattaforma farà incontrare necessità e soluzioni.”

Master thesis (Internship) CNH

March 25, 2020

Intership/Master thesis proposal

Development and Assessment of a Predictive Cruise Control for Heavy Duty Vehicles

Background

For heavy-duty vehicles, fuel consumption is among the highest running costs. Hence, systems aiming at reducing fuel consumption have the highest impact on the development of modern heavy-duty vehicles.

Although developing and optimizing engine and powertrain technologies continuously leads to a reduction of fuel consumption, alternative approaches can be used, which rely on the optimization of the vehicle operation based on the information about the surrounding environment. Predictive Cruise Control (PCC) automatically regulates the vehicle speed based on the information about, e.g., the traffic ahead along the desired route and the road slope, thus minimizing unnecessary vehicle accelerations and contributing to reducing the overall fuel consumption.

Problem description and objectives

Predictive Cruise Control systems can differ in the amount and type of information about the surrounding environment and the vehicle actuators used to control the vehicle longitudinal motion. The objective of this thesis work is the re-design and the assessment of the Predictive Cruise Control developed at CNH, in order to add the engine shut-off to the used actuator set. Finally, the designed Predictive Cruise Control system will be integrated in CNH full vehicle models and tested on different homologation and user-defined cycles.

We are searching for

Teams of max. 2 highly motivated students with a basic background in automatic control, modeling of vehicle dynamics, signal processing. Good knowledge of Matlab/Simulink and basic programming skills are welcome.

Contacts:

Paolo Falcone, tel.: +39 059 205 6301, falcone@unimore.it

Luigi Biagiotti, tel.: +39 059 205 6315, luigi.biagiotti@unimore.it

Laura Giarrè, tel.: +39 059 205 6322,  laura.giarre@unimore,.it

Roberto Zanasi, tel.: +39 059 205 6161, roberto.zanasi@unimore.it

Gaetano Bonavolontà, tel.: +39 059 591674, gaetano.bonavolonta@cnhind.com

 

An other interesting article

March 13, 2020

https://www.dropbox.com/s/esutbuhk29gopak/note_covid_model.pdf?dl=0

March 12, 2020

youtu.be/ruIJ9veahwA

Analysis of data by de Nicolao

Call for Master Thesis

November 27, 2019

Mixed model-based and data-driven control of miniature race cars

Purpose and aims
The goal of this master thesis project is to develop and demonstrate, with scale
testing vehicles, an estimate and control architecture executing motion planning and
control algorithms for racing applications.

Problem description

The problem proposed in this thesis work is to design estimation, motion planning and control algorithms for scaled race vehicles. The sensors and actuators setup and the vehicle model have to reflect existing prototypes of the scaled vehicles.

Master thesis proposal Unimore – race cars

 

New paper accepted

November 19, 2019

Our work has been accepted for publications on IEEE ACCESS:

An indoor and outdoor navigation system for visually impaired people
Daniele Croce∗¶, Laura Giarré†, Federica Pascucci‡, Ilenia Tinnirello∗, Giovanni Galioto∗, Domenico Garlisi§, Alice Lo Valvo∗

∗DI, Università di Palermo, Viale delle Scienze, ed. 9, 90128 Palermo, Italy

†DIEF, Univ. di Modena e Reggio Emilia, Via P. Vivarelli, 10, 41125 Modena, Italy (Senior Member, IEEE)

‡DI, Università Roma Tre, Via della Vasca Navale, 79, 00146 Roma, Italy §CNIT Consortium, Viale G.P. Usberti, 181/A – 43124 Parma, Italy

¶CS Dept., Università di Roma “La Sapienza”, Via Salaria 113 – 00198 Rome, Italy

The authors acknowledge In.Sight s.r.l. (https://in.sight.srl) for developing the localization system (patented [5])

ABSTRACT

In this paper, we present a system that allows visually impaired people to autonomously navigate in an unknown indoor and outdoor environment. The system, explicitly designed for low vision people, can be generalized to other users in an easy way. We assume that special landmarks are posed for helping the users in the localization of pre-definedpaths. Our novel approach exploits the use of both the inertial sensors and the camera integrated into the smartphone as sensors. Such a navigation system can also provide direction estimates to the tracking system to the users. The success of our approach is proved both through experimental tests performed in controlled indoor environments and in real outdoor installations. A comparison with deep learning methods has been presented.

Special issue on Sensor based Smart Grid in Internet of Things Era

April 1, 2019

Please join us in publishing a contribution to SENSORS on:

Sensor based Smart Grid in Internet of Things Era

The smart grid is an innovative energy network able to improve the conventional electrical grid so to be more reliable, cooperative, responsive, and economical. The smart grid can be regarded as an enabling technology to let the existent cities ready for tomorrow needs.

Within its new capabilities, advanced data sensing, communication, and networking technology are playing significant roles in shaping the future smart grid. Exploiting the Internet of Things technologies paradigm, smart grid technology improves two-way communication between utility companies and customers and allows access to near real-time data that can be used to make cost-effective and environmentally friendly decisions. The IoT approach opens new challenges, such as, for example, designing new sensors, collecting and transmitting information, making intelligent decisions, and optimizing loads. A world of connected assets, meters and substations, vehicles, and devices is the key to a future efficient and reliable smart grid. Not only the smart grid needs to be thought of in terms of vertical applications, but cities and citizens of cities need to be empowered as actors in this revolution.

The aim of the present Special Issue is to investigate all the aspects related to this new connected world, in terms of optimization, communication, control, design, and distribution, with a particular emphasis on the use of IoT solutions.

We encourage authors to submit their interdisciplinary contributions in this area.

Prof. Dr. Laura Giarre
Prof. Dr. Federica Pascucci
Guest Editors