[robotics-worldwide] PhD position in robot learning, Department of Advanced Robotics, Italian Institute of Technology (IIT)

Petar Kormushev Petar.Kormushev at iit.it
Thu Aug 16 09:24:15 PDT 2012


** PhD position in machine learning for robot locomotion **
** PhD Theme: Developmental robotics and robot learning for agile locomotion of compliant humanoid robots  **

The Learning and Interaction Lab, Department of Advanced Robotics, Italian Institute of Technology (IIT) has one PhD opening in the field of machine learning for robot locomotion. The position is fully funded, starts in January 2013 and typically lasts 3 years.

IIT is an English-language research institute located in Genoa, Italy. Knowledge of Italian language is NOT a requirement. International applications are encouraged and will receive logistic support with visa issues.

For additional information: http://kormushev.com/news/open-phd-positions-in-robotics-at-iit-for-2013/

Application website: http://www.studenti.unige.it/postlaurea/dottorati/xxviiiciclo/IITen

Application deadline: September 21, 2012 (12 noon, Italian time)

Application requirements:

Strongly-motivated candidates holding a Master degree in Computer Science / Engineering / Mathematics or other related fields are invited to apply. Applicants should ideally have a background in machine learning, robotics or human-robot interaction, with strong mathematical and computer programming skills (Matlab, C++ or equivalent).

Application procedure:

To apply please send a detailed CV, a cover letter, BSc and MSc transcripts, and at least two reference letters to Dr Petar Kormushev (petar.kormushev at iit.it), including the tag [PhD2013] in the email's subject. The applicants also need to fill the online application form of the University of Genova: http://www.studenti.unige.it/postlaurea/dottorati/xxviiiciclo/IITen


The details of the PhD position are as follows:

*** STREAM 1: Machine Learning, Robot Control and Human-Robot Interaction (Advanced Robotics - Prof. Darwin Caldwell)

** Theme 3.1: Developmental robotics and robot learning for agile locomotion of compliant humanoid robots 

** Tutor:  Dr Petar Kormushev, Dr Nikos Tsagarakis 

Developmental robotics offers a completely different approach for controlling humanoid robots than the currently predominant approach based on manually engineered controllers. For example, currently, the majority of bipedal walking robots use variants of ZMP-based walking with largely simplified models of the robot dynamics. As a result, despite the significant mechatronic advances in humanoid robot legs, the locomotion repertoire of current bipedal robots merely includes slow walking on flat ground or inclined slopes, and primitive forms of disturbance rejection. This is far behind from even a two-year old child.

The creation of novel, high-performance, passively-compliant humanoid robots (such as the robot COMAN developed at IIT) offers a significant potential for achieving more agile locomotion. However, the bottleneck is not the hardware anymore, but the software that controls the robot. It is no longer reasonable to use over-simplified models of robot dynamics, because the novel compliant robots possess much richer and more complex dynamics than the previous generation of stiff robots. Therefore, a new solution should be sought to address the challenge of compliant humanoid robot control.

In this PhD theme, the use of developmental robotics and robot learning methods will be explored, in order to achieve novel ways for whole-body compliant humanoid robot control. In particular, the focus will be on achieving agile locomotion, based on robot self-learned dynamics, rather than on pre-engineered dynamics model. The PhD candidates will be expected to develop new algorithms for robot learning and to advance the state-of-the-art in developmental robotics.

The expected outcome of these efforts includes the realization of highly dynamic bipedal locomotion such as omni-directional walking on uneven surfaces, jumping and running robustly on uneven terrain and in presence of high uncertainties, demonstrating robustness and tolerance to external disturbances, etc. The ultimate goal will be achieving locomotion skills comparable to a 1.5 - 2 year-old child.

Requirements: This is a multidisciplinary theme where the successful candidates should have strong competencies in machine learning and artificial intelligence, and good knowledge of robot kinematics and dynamics. The candidates should have top-class degree and a background in Computer Science, Engineering, or Mathematics. Required technical skills: C/C++ and/or MATLAB. Knowledge of computer vision is a plus.

For further details please contact petar.kormushev at iit.it, including the tag [PhD2013] in the email's subject.

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Petar Kormushev, PhD 
Team leader - Learning and Interaction Lab
Department of Advanced Robotics
Italian Institute of Technology (IIT)
Via Morego 30, 16163 Genoa, Italy

http://kormushev.com
http://www.iit.it/advr
http://www.iit.it/en/advr-labs/learning-and-interaction.html
http://www.iit.it/en/people/advanced-robotics/team-leader/petar-kormushev.html

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In order to comply with the Italian law (art. 23 of Privacy Law of the Italian Legislative Decree n. 196/03), we have to kindly ask the candidate to give his/her consent to allow us to process his/her personal data. We inform you that the information you provide will be used solely for the purpose of assessing your professional profile to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, with headquarters in Genoa, Via Morego 30, acting as the Data Holder, using computer and paper based means, observing the rules on protection of personal data, including those relating to the security of data. Please also note that, pursuant to art.7 of Legislative Decree 196/2003, you may exercise your rights at any time as a party concerned by contacting the Data Manager.




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