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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

 

 

CHI conference

March 11, 2019

At the CHI’19 workshop

HACKING BLIND NAVIGATION

A CHI’19 workshop to discuss and tackle open challenges of independent navigation of blind people

We will present the following contribute:

Toward an Open Platform of Blind Navigation via Interactions with
Autonomous Robots

Authors

Ni-Ching Lin
National Chiao Tung University
Hsinchu 300, Taiwan
niching.ece05g@g2.nctu.edu.tw
Shih-Hsing Liu
National Chiao Tung University
Hsinchu 300, Taiwan
c52647.ece07g@nctu.edu.tw
Yi-Wei Huang
National Chiao Tung University
Hsinchu 300, Taiwan
d3637042.eecs02g@g2.nctu.edu.tw
Yung-Shan Su
National Chiao Tung University
Hsinchu 300, Taiwan
michael1994822.ece06g@nctu.edu.tw
Chen-Lung Lu
National Chiao Tung University
Hsinchu 300, Taiwan
eric565648.eed03@g2.nctu.edu.tw
Wei-Ting Hsu
National Chiao Tung University
Hsinchu 300, Taiwan
thpss92093.eed04g@nctu.edu.tw
Li-Wen Chiu
National Chiao Tung University
Hsinchu 300, Taiwan
lili0519.ece07g@nctu.edu.tw
Santani Teng
The Smith-Kettlewell Eye Research Institute
San Francisco 94115, USA
santani@ski.org
Laura Giarré
Università di Modena e Reggio Emilia
Modena 41125, Italy
laura.giarre@unimore.it
Hsueh-Cheng Wang
National Chiao Tung University
Hsinchu 300, Taiwan
hchengwang@g2.nctu.edu.tw

 

Visiting IDI

February 20, 2019

From Febraury 15th to February 19th, 2019 I’ve been visiting IDI @NTNU.

During the Visit, I was working with Prof. L. Jaccheri and we had research meetings on Storytelling and Women Mentoring.

I also met prof. F. Lindseth that described me his autonomous driving projects.

 

 

 

Seminar prof. Falcone

October 16, 2018

Avviso di seminario

Mercoledì 17 ottobre 2018, ore 14.30

Sala Riunioni. edificio 27, Dief

 Control Invariance Tools for Control Design with Performance Guarantees with applications to highly automated transportation systems

Paolo Falcone

Department of Electrical Engineering, Chalmers

University of Technology, Gothenburg, Sweden

falcone@chalmers.se

 Keywords

Vehicle lateral control, Multi-vehicle systems, Networked control systems, Joint communication and control design

Abstract

Control invariance is a property of dynamical systems state sets, which is widely used in control design for constrained systems. If a system state trajectory starts in a control invariant set C, it will be always possible to find an admissible control input keeping the system state trajectory within C. Hence, if the system constraints are defined w.r.t. to the required performance (e.g., maximum accepted bounds on the tracking errors), control invariant sets can be used to design control laws with performance guarantees. In this talk, we will highlight a few computational aspects related to control invariant sets and present recent results from their applications to a vehicle motion control problem and to the control of a multi-vehicle system over a wireless network. In Level-4+ autonomous vehicles, a human driver will not be available to back up the vehicle control system anymore. Hence, the overall autonomous driving system should be designed in order to provide performance and safety guarantees. Such stringent requirements can be translated into constraints in Model Predictive Control (MPC) control schemes. Moreover terminal control invariant set constraints can be used to enforce the persistent feasibility of the underlying optimization problem, at the cost of possible increased computational complexity. In this talk, we will show how low-complexity invariant sets can be derived thanks to newly developed methods and how these can be used as an additional tuning tool to trade off the MPC controller complexity for the size of its feasibility set. The next challenge, beyond high-level autonomous driving, is the cooperation of autonomous vehicles. Nevertheless, the safety and performance issues arising from the tight coupling between communication and control must be accounted for at the design stage. Starting from a multi-vehicle coordination problem at traffic junctions, we will motivate a joint communication and control paradigm, where a central coordinator decides upon control inputs to a set of dynamical systems and their access to the communication channel. We will show a few results from numerical examples and new research directions.

Bio. Paolo Falcone received his M.Sc. (“Laurea” degree) in 2003 from the University of Naples Federico II and his Ph.D. degree in Information Technology in 2007 from the University of Sannio, in Benevento, Italy. He is Bitradande Professor (Professor) at the Department of Electrical Engineering of the Chalmers University of Technology, Sweden. His research focuses on constrained optimal control applied to autonomous mobile systems, cooperative driving and intelligent vehicles. He is involved in several projects, in cooperation with the Swedish automotive and ICT industries, focusing on autonomous driving, cooperative driving and vehicle dynamics control.

Round table AUTOMATICA beyond Engineering @ automatica.it

September 17, 2018

Here the slides of the Round Table (my introduction) on Automatica beyond Engineering