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Summer School on Control and Robotics: Fundamentals for advanced research 23 - 24 Julho 2018

Porto


Summer School on Control and Robotics: Fundamentals for advanced research

 

Summer School on Control and Robotics: Fundamentals for advanced research

The goal of the Summer Course is to present in a tutorial and accessible way to the largest number of doctoral students and researchers key mathematics tools that supports advanced engineering in Robotics and Control.

 

Topics & Lecturers:

  • Nonlinear Control

António Pedro Aguiar

  • Functional Analysis

Fernando Lobo Pereira

  • Control of Robotic Manipulators

Rui Cortesão

  • Sparse Optimization and Image Processing

Mário Figueiredo

 

To Whom?

phD students and Researchers in Mathematics, Economics, Mechanical, Electrical or other Engineering or related fields.

 

How to apply?

Send a pre-registration email with your personal data, course graduation, and contact to:

João Miranda Lemos, jomlemos@gmail.com.

 

Deadlines

Pre-registration: 15 May 2018

Notification of acceptance: 31 May 2018

Send payment confirmation: 30 June 2018

 

How much?

50 euros fee

 

When?

23-24 July 2018

 

Where?

FEUP Room I-105 (9h-17h) Campus da FEUP

Rua Dr. Roberto Frias

4200 - 465 Porto, Portugal

 

Lecturers:

  • Nonlinear Control

António Pedro Aguiar

Link to personal page:



Biographical note

 

Summary of the Presentation:

 

 

  • Functional Analysis

Fernando Lobo Pereira

Link to personal page:



Biographical note

 

Summary of the Presentation:

 

  • Control of Robotic Manipulators

Rui Cortesão

Link to personal page:

http://home.isr.uc.pt/~cortesao/

Biographical note

Rui Cortesão received the B.Sc. ("Licenciatura") degree in Electrical Engineering, M.Sc. degree in Systems and Automation and Ph.D. degree in Control and Instrumentation from the University of Coimbra, Portugal, in 1994, 1997 and 2003, respectively. He was visiting researcher at the German Aerospace Center - DLR (1998-2003), where he did his Ph.D. work, Stanford University (2002), LIRMM-CNRS (2004, 2006, 2008), and Barrett Technologies (2007), having worked on surgical robotics, haptic tele-manipulation, compliant motion control, data fusion and human-robot skill transfer. Rui Cortesão is the Head of the medical robotics group with the Institute of Systems and Robotics - University of Coimbra, Professor of the University of Coimbra and Director of IPN-LAS.

 

Summary of the Presentation:

This talk addresses the foundations of computed torque control of robot manipulators, for both free space and constrained motions. Dynamic modelling, resolved acceleration control, non-linear feedback linearization, and compliance control techniques will be discussed. Medical applications will be presented, showing the relevance of robot manipulators in emerging areas.

 

  • Sparse Optimization and Image Processing

Mário Figueiredo

Link to personal page:

http://www.lx.it.pt/~mtf/

Biographical note

Mário A. T. Figueiredo received a PhD degree in electrical and computer engineering, from Instituto Superior Técnico (IST), the engineering school of the University of Lisbon, in 1994. He has been with the faculty of the Department of Electrical and Computer Engineering, IST, since 1994, where he is now a Professor. He is also area coordinator and group leader at Instituto de Telecomunicações.

His research interests include image processing and analysis, machine learning, and optimization. He is a Fellow of the IEEE and of the IAPR and has been included, since 2014, in the Highly Cited Researchers list produced Clarivate Analytics and formerly by Thomson Reuters. He received several awards, namely the 2011 IEEE Signal Processing Society Best Paper Award, the 2014 IEEE W. R. G. Baker Award, the 2016 EURASIP Individual Technical Achievement Award, and the 2016 IAPR Pierre Devijver Award.

Summary of the Presentation:

This tutorial will cover the mathematical foundations of the convex optimization tools and methods that are used to deal with the optimization problems that arise in image processing with sparsity-inducing regularizers. These problems are characterized by high dimensionality and non-smoothness, which has stimulated a large amount of research and advances in this area.