Doctoral Course on “Robotics, Cognition and Interaction Technologies”
Call for PhD students for 2013
PhD positions with scholarships are available at the Italian Institute of Technology (IIT) in Genoa, Italy.
Doctoral course starting in January 2013
Application deadline: September 21, 2012
Online application here
Please note that IIT is an English-language research institute, so it is not required to speak Italian.
I have one PhD opening in my team, in the field of Reinforcement Learning with application to Robot Control. The details can be found in Annex A4 – Doctoral course on “Robotics, Cognition and Interaction Technologies”, and are as follows.
[Section 3. Department of ADVANCED ROBOTICS – PROF. DARWIN CALDWELL]
STREAM 1: Machine Learning, Robot Control and Human-Robot Interaction
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 about this particular PhD position, please contact me by e-mail.