The Department of Industrial Engineering in cooperation with the School of Innovation, University of Trento (Italy), organize the first edition of the Winter School on Innovation in Autonomous Systems (WSIAS 2020).
The goal of the School is to provide M.Sc. or Ph.D. students, young researchers and professionals with a wide range of lectures with state-of-the-art contents and other activities led by some of the most prominent researchers in the field of autonomous systems for industrial applications and professional innovators shaping the industrial applications of the future, thus helping attendees to bridge the gap between different and complementary subjects. The School offers also a great opportunity not only to learn new skills, but also to create new connections between attendees and lecturers and to share experiences.
The theme of the WSIAS 2020 is Next Industry Generation.
The School will be activated if a minimum of 10 participants is reached. The maximum number of attendees is instead fixed to 25.
The WSIAS 2020 will be held at the University of Trento, from January 27 to January 31, 2020. The venue will be at the Polo Scientifico e Tecnologico "Fabio Ferrari", via Sommarive 5, Trento (Italy)
Autonomous systems are pervading the modern society. They are the result of a fusion of sensors, automation, computers, and communication technologies that affects all areas of engineering. The goal of this highly interdisciplinary research field is to develop intelligent systems that can interact dynamically with the complexities of the real world and, handling big data, make independent decisions about how to act, even collectively, especially in unplanned, changing, or unexpected conditions. Due to the potential disruptive impact on almost every aspect of life, business, industry, health and education, autonomous systems are becoming a huge and highly competitive market that have attracted the recent attention of some of the biggest and fastest-growing companies in the world. Indeed, autonomy promises to do things that could not be done before, or to do existing operations more efficiently or safely, thus redefining work or improve work conditions for humans and reduce the need for human contribution.
The main goal of the School is to provide graduate and doctoral students with state-of-the-art skills in the exciting and broad research field of Autonomous systems, thus helping them to bridge the gaps between different and complementary subjects.
In particular, the School aims at:
The School covers key subjects and topics in the area of Autonomous Systems for Industrial Applications.
The lectures of the School will be in English.
The School is expected to provide contents in the following relevant topics:
Here follows the Programme
> 19:30 Social Dinner
By modelling driving as a Perception-Action (PA) hierarchy it is possible to combine high-level symbolic logical reasoning (in particular, the Highway Code applied to hypothetical road configurations) with low-level sub-symbolic processes (specifically, Optimal Control and stochastic machine learning). In this talk I will outline the motivations for the perception-action approach, and propose a number of models including a cortical frontal loop analogue for autonomous vehicles in which progressively-abstracted bottom-up scene understanding is followed by top- down legal action specification (with progressive contextual grounding), such that final action selection is carried out via simulated basal ganglia model. Although the top level of the PA- hierarchy employs explicit first-order logical reasoning we explore inductive mechanisms such that the PA hierarchy can learn adaptively at all levels.
Dr. David Windridge is Associate Professor in Computer Science at Middlesex University, UK and leads the Dept. of Computing's Data Science activities. His research interests centre on practical and theoretical development in machine learning, cognitive systems and computer vision (he also has a former research interest in astronomy/astrophysics). He has authored more than 100 academic publications in these areas and played a leading role on a number of large-scale machine-learning projects in academic and industrial research settings (including the DREAMS4CARS, ACASVA and DIPLECS projects centring on hierarchical perception-action learning and its practical application to areas including autonomous vehicles and driver assistance systems). He has also won interdisciplinary research grants in areas such as psychological modelling and proteomic classification (his work in the application of healthcare analytics to 3d laparoscopic surgery received national UK media coverage). He is Visiting Associate Professor at the University of Surrey, UK and sits on the editorial board of the Springer journal Quantum Machine Intelligence.
Markets are volatile, customer tastes continuously changing and product lifecycles shorter and shorter. The only way to survive, and eventually, win in this environment is to have an obsessive attention to the customer. It is essential to know his/her needs and their trends. Once you have a full empathy with your customer and know her/his problems, you can leverage on your domain knowledge and unleash your creativity to find a solution with a value added higher than what currently available in the market. We will experience together the CPS (Customer, Problem, Solution) canvass until participants will be able to internalize it completely.
Vittorino Filippas, former top manager, free lance, international re-startupper, innovator, business developer and Fantic Motor shareholder. I carve some time from my company to act as lecturer and mentor at the University of Trento. I coach students, startuppers, entrepreneurs, and top managers in the fileds of innovation, internationalization and entrepreneurship. People say I am an enthusiast and energetic motivator both at University, in my Company and at TEDx events https://www.youtube.com/watch?v=kFh3Q2eOZ1U&t=622s and https://www.youtube.com/watch?v=2snxLdYIY2k
This module aims at teaching participants on how to ideate hi-tech products, services and systems capable of impacting on clear users needs. First, participants will be trained in utilizing the design thinking methodology and the Design Sprint to identify specific use cases for the technologies featuring autonomous systems, and create promising ideas of hi-tech products or services. Second, by getting to know the principles underpinning good design, participants will learn how to turn ideas into concepts and early prototypes acting as a basis to develop products and services with a great user experience.
Nicola holds an Executive Master in Management at MIP - Politecnico di Milano School of Business and a Master degree in Sociology. He works at Hub Innovazione Trentino, a technology transfer and innovation management foundation in northern Italy. Nicola is responsible for designing and managing open innovation initiatives connecting companies with researchers and students. He coordinates H2020 European-wide research and innovation projects on topics such as open innovation and design-driven innovation. He coaches startups and young talents on matters such as design thinking, service design, user experience design, product development and innovation strategy. Previously Nicola has managed a team in charge of supporting ICT research centres, universities and large European digital companies to design and test hi-tech products along with end-users.
Radar technologies, already widely used in modern vehicles for increasing the level of safety and reducing the risks, will certainly represent one the key enabling technology for next generation automotive systems. Indeed, in a near future, a number of car models will be equipped with several radar-based sensors allowing a complete 360 degrees view of the surroundings, thus increasing the driver assistance services as well as the semi-autonomous operations.
In this framework, the request for high-precision, low-cost, and multi-function radar systems is constantly growing and is higher than ever before. Towards this aim, both the academic and the industrial worlds are deeply involved in developing new research activities and proposing innovative technologies able to address the challenging requirements and constraints.
In this lectures, starting from the fundamentals of radar systems and their operation in the context of current automotive systems, a review of the most recent technological solutions, mainly based on frequency-modulated continuous-wave (FMCW) radar, will be presented. Afterwards, some new trends in automotive radar (e.g., MIMO radar) will be discussed, in which improved hardware and software solutions enabling the use of higher frequencies, larger bandwidths, and multiple transmit and receive channels are exploited as additional degrees of freedom for the radar operation.
Paolo Rocca received the MS degree in Telecommunications Engineering from the University of Trento in 2005 (summa cum laude) and the PhD Degree in Information and Communication Technologies from the same University in 2008. He is currently Associate Professor at the Department of Information Engineering and Computer Science (DISI) of the University of Trento (UniTN) and director of the ELEDIA Research Center (ELEDIA@UniTN – DISI). Moreover, he is Visiting Professor at the Xidian University, Xi'an, China.
Prof. Rocca has been a visiting Ph.D. student at the Pennsylvania State University (U.S.A.), at the University Mediterranea of Reggio Calabria (Italy), and a visiting researcher at the Laboratoire des Signaux et Systèmes (L2S@ Supèlec, France) in 2012 and 2013. Moreover, he has been an Invited Professor at the University of Paris Sud (France) in 2015 and at the University of Rennes 1 (France) in 2017. He has been awarded from the IEEE Geoscience and Remote Sensing Society and the Italy Section with the best PhD thesis award IEEE-GRS Central Italy Chapter.
Prof. Rocca is the author/co-author of more than 370 scientific contributions, of which more than 120 journal papers, mainly focused on radar, communications, and microwave imaging technology. His main research interests are in the framework of artificial intelligence techniques as applied to electromagnetics, antenna systems for radar and communications, and electromagnetic inverse scattering. He has been and is the principal investigator of 17 technology transfer projects with qualified national and international partners, including companies leader in the ICT context at international level.
Alessandro Rossi, University of Trento, Italy
- Business model definition and typologies
- Business modelling and strategies in the automotive industries: Which opportunities?
- At the crossroad of well-being, mobility, and automotive: Overview and discussion over new trends
- New players and business opportunities: who against whom?
Speaker Bio: Alessandro Rossi, ph.D., is Associate Professor in Management at the Department of Economic and Management (University of Trento), has research interests in innovation management, business modelling, entrepreneurship and decision making. He is the I&E Coordinator for the Trento EIT Digital Industrial Doctoral School and the Chief of Contamination Lab Trento, a UniTrento educational coworking space which aims at fostering academic education on soft skills, creativity, innovation, entrepreneurship and intrapreneurship, complementing standard academic curricula by employing teaching methods based on laboratorial learning, problem-based learning, teamwork, and coaching by entrepreneurs. He is the main instructor of “Start-Up Lab”, an elective graduate class on new venture creation, aimed at helping students develop an entrepreneurial approach to problems and the ability to search effectively for user-centric innovative solutions.
Robotic instruments are miniature robots and mechatronic systems that can manipulate small objects and precisely interact with different surfaces. In this talk, I will discuss our recent work in robotic instruments, including: acoustic manipulation devices that can automatically manipulate a large amount of objects on surface using a single transducer; robotic electromagnetic needle that can precisely manipulation and assemble magnetic microparticles by contact or contactless; scanning droplet adhesion microscope that can map the wetting properties of surfaces; and devices that can manipulate and deposit nanoliter droplets on patterned surfaces. This talk will cover both robotic mechatronics and automation/autonomous aspects.
Quan Zhou received the M.Sc. degree in Control Engineering and Dr. Tech. degree in Automation Technology, both from Tampere University of Technology, Tampere, Finland. Currently, he is a tenured Associate Professor at the Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, Finland, heading the Robotic Instruments group. He was a Professor at Northwest Polytechnical University, Xi’An, China. His main research interests are micro-and nano manipulation and automation methods. His work has been published in major international journals including Nature Communications, Physical Review Letters, Advanced Materials, Small and IEEE Transactions on Robotics. Prof. Zhou has won the 2018 Anton Paar Research Award for Instrumental Analytics & Characterization. He was the general chair of International Conference of Manipulation, Automation and Robotics at Small Scale, MARSS 2019. He is also serving as the topic editor in chief on micro- and nanorobotics for the international journal of advanced robotic systems, and member of editorial board of journal of micro-bio robotics. He was an associate editor of journal of micro-nano robotics, and guest editors in several journals including IEEE transaction on automation science and engineering. Dr. Zhou was also the coordinator of EU FP7 project FAB2ASM, the first PPP project of the European Economic Recovery Plan. He was the chair of IEEE Finland Joint Chapter of Control System Society, Robotics and Automation Society and System Man and Cybernetics Society.
Sensors provide the primary source of information for autonomous driving.
Autonomous vehicles need and use sensors to gather information about their environment. Self-driving cars have to make "autonomous" actions, "intelligent" decisions, they have to react to their environment for which first they have to have information about it. To have information about the environment one has to "sense", measure the environment. Autonomous cars have to interface with their environment which is happening via sensors tasked with sensing and making measurements. The challenge in the autonomous vehicle sensors is to provide enough, relevant, up to date ("real-time"), reliable, precise, accurate, if possible easy to process information covering "all” important aspects of the environment and traffic. Nowadays, among the existing solutions not a single sensor is able to provide such information, and despite the rapid development, the current mechanisms have several limitations. Thus, several redundant, different type of sensors are used to provide "pieces" of information, which then in turn has to combine together to create a model of the environment and to be able to make driving decisions. This lecture gives an introductory overview of the sensors used for autonomous driving.
Dr. Zoltán Istenes received his PhD in 1997 at Nantes, France, and he is working ever since at the Eötvös Loránd University, Faculty of Informatics (ELTE, Budapest, Hungary). As an associate professor his main teaching and research interests includes computer architectures, artificial intelligence, robotics, IoT, UAVs, formal methods, and recently autonomous self-driving vehicles. He participated and managed several national and international research projects. Founder member and head of the John von Neumann Computer Society Robotics section. Since 2010, he is part of the EIT Digital, where he is now leading the EIT Digital Budapest Doctoral Training Centre and advising the head of the EIT Digital Industrial Doctoral School organizing and managing the education, research and business activities of the PhD students. Also, he is the local coordinator of the EIT Digital Master School Autonomous Systems major in Budapest.
This lecture is dedicated to methodologies for information analysis and integration that are based on applied ontology. We will start showing problems that arise when information is not classified correctly and problems that arise when models are too application specific. Then we will show how the use of ontological analysis (e.g., mereology and dependence theory) and ontological modeling (e.g. the OntoClean methodology) overcome these problems. Finally, we discuss how the ontological approach is influencing the development of autonomous robots and engineering systems at large, including ongoing work in some international standardization groups.
Stefano Borgo (Laurea and M.A in Mathematics; M.S and PhD in Computer Science) is head of the Laboratory for Applied Ontology, a unit of the Institute of Cognitive Sciences and Technologies (ISTC), part of the National Research Council (CNR). He studied at the University of Padua (Laurea), Indiana University (M.A. and M.S.) and the Free University of Bolzano-Bozen (PhD). His research focuses on ontology and its application in information structuring and modeling methodologies with applications in robotics, cyber-physical and socio-technical systems. Areas of application include engineering design, product and process modeling, laboratory data, urban planning and architecture. He co-authored the DOLCE ontology and has been active in about 30 national and international projects. He is member of the Editorial Board of the Applied Ontology journal, of the Semantic Web Journal, and of the Advisory Board of the International Association on Ontology and its Applications (IAOA) where in the past he served in the Executive Council. He is also member of standardisation ISO and IEEE working groups. In 2010 he has been appointed professor at the Institute of Scientific and Industrial Research of Osaka University.
In general, full-time student attendance is required to complete the School.
Single day registration and attendance is possible only for senior researchers and/or professionals from companies.
At the end of the School participants will receive a certificate of attendance; the certificate will be issued upon verification of the signatures daily taken during the classes.
Target audience and eligibility
The School is open to both students and practitioners interested in learning the most recent advancements in the broad area of autonomous systems for industrial innovation.
The primary audience of the School includes last-year M.Sc., Ph.D. students, young researchers and professionals with a background in engineering or other scientific disciplines. Engineers and technicians employed in universities, research centers or companies are also invited to apply. All of them may greatly benefit from the broad vision provided by the School.
Admission to the School is decided on the basis of the applicant's background and curriculum vitae (CV). The CV and a motivational letter will have to be uploaded through the online application form and should be preferably prepared according to the EUROPASS format
Non-EU citizens will be required to upload (through the online application form) a copy of their valid permit of stay for EU Countries or a copy of their passport (with Schengen visa, if required).
All applicants have to register online only.
The School is free of charge for Students
Practitioners are supposed to pay:
- € 300 to take part in the whole School or
- € 100 for each Single Day
The registration includes:
Dinners other than the social dinner, accommodation and transportation costs are not covered.
Applicants will be selected on CV and motivation basis, admission will be communicated by email.REGISTER HERE
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