Name: Petar Kormushev
Member since: 2010-09-25 15:46:41
Last Login: 2013-06-21 10:25:11
Petar Kormushev is a senior postdoctoral researcher at the
Advanced Robotics department of the Italian Institute of
Technology, doing research on the iCub humanoid robot and a
Barrett WAM robot.
In 2009 he graduated with a PhD degree in Computational
Intelligence from Tokyo Institute of Technology. His
research interests include robotics and machine learning,
especially reinforcement learning for intelligent robot
He holds a MSc degree in Artificial Intelligence, a MSc
degree in Bio- and Medical Informatics, and a BSc degree in
Computer Science from Sofia University. He has participated
in many scientific projects, including European INFRAWEBS
project for designing the future Semantic Web, and Japanese
NEDO project for developing a common basis for next-
He has won a number of prestigious awards, including a
“John Atanasoff” award, a “St. Kliment Ohridski” award, and
a 4-year Monbukagakusho/MEXT Japanese research fellowship.
Recent blog entries by Petar.Kormushev
Contest for John Atanasoff award in 2014
Sorry, this entry is only available in Български.
Kangaroo robot by Festo
An amazing robotic Kangaroo made by Festo!
(excerpt from Ludmila Kuncheva’s page)
“Reviewing will become obsolete. It has been needed in the past because there has been no way to tap on a larger readers’ audience for an opinion poll. Peer reviewing has been the only credible way to maintain standards of publication. The growing diversity of topics makes this process impractical, biased or spurious. We have technology now! We can allow for peer reviewing on a massive scale. Imagine a large pool of papers, automatically clustered and positioned within a big mosaic. Where do you look for papers? I doubt very much that you browse the contents of all relevant journals. Thank God for Internet! Now suppose that you have access to all papers. The best ones will be spotted and cited over and over. The citations will replace the reviews.
There will be fewer journals such as Nature, Science and Lancet. Only the best papers will find their place in the journals. These papers will no longer be original research, they will be rather “the best of…”. Selected by citation from the pool, say for the past 1 year, these papers can undergo a round of peer review. This time, however, the reviewing rules will be different:
- First, all reviews will be handsomely paid.
- Second, reviewers will bid for a paper. The candidates should submit their records, and the Editor will have the task to select among them.
As an additional benefit, we will kill fewer trees. Plus, a lot of human resource will be freed for better use of their expertise and energy. “
IEEE Technical Committee on Robot Learning
The robot hardware is progressively becoming more complex, which leads to growing interest in applying machine learning and statistics approaches within the robotics community. At the same time, there has been a growth within the machine learning community in using robots as motivating applications for new algorithms and formalisms. Considerable evidence of this exists in the use of robot learning approaches in high-profile competitions such as RoboCup and the DARPA Challenges, and the growing number of research programs funded by governments around the world. Additionally, the volume of research is increasing, as shown by the number of robot learning papers accepted to IROS and ICRA, and the corresponding number of learning sessions.
learning models of robots, tasks or environments
learning deep hierarchies or levels of representations, from sensor and motor representations to task abstractions
learning of plans and control policies by imitation and reinforcement learning
integrating learning with control architectures
methods for probabilistic inference from multi-modal sensory information (e.g., proprioceptive, tactile, vison)
structured spatio-temporal representations designed for robot learning such as low-dimensional embedding of movements
developmental robotics and evolutionary-based learning approaches
- [May 21, 2013] New Job opening – Post-doc in Robot Learning on topic: “Machine Learning for Robotics”. Details here: http://kormushev.com/news/postdoc-opening-in-machine-learning-for-robotics-2013/
[August 10, 2012] New IROS 2012 Workshop: “Beyond Robot Grasping – Modern Approaches for Dynamic Manipulation”. The workshop will be held on October 12, 2012 in Algarve, Portugal. More information at the website of the workshop: http://www.ias.informatik.tu-darmstadt.de/Research/IROS2012
[March 28, 2012] New AIMSA 2012 Workshop organized by the TC on “Advances in Robot Learning and Human-Robot Interaction”. The workshop will be held on September 12, 2012 in Varna, Bulgaria. More information at the website of the workshop: http://kormushev.com/AIMSA-2012/
[March 13, 2012] New chairs of the TC. After three very successful years for this TC on Robot Learning, the founding chairs Jan Peters, Jun Morimoto, Russ Tedrake and Nicholas Roy are stepping down as chairs of the committee. They will be replaced by Petar Kormushev, Edwin Olson, Ashutosh Saxena, and Wataru Takano who have kindly agreed to take the reign of the committee. Please see the changes in the mailing list addresses here.
Recent Activities of the Technical Committee
The technical committee regularly organizes special sessions associated with the “Robot learning” RAS keyword. If you want your paper to be considered for such a session and have used the above keyword in your submission, please forward an email to the TC co-chairs (contact info at: http://www.ieee-ras.org/robot-learning/contact). The technical committee will not be involved in the reviewing process but will organize the session based on the list of accepted submissions with this keyword.
This is a summary of the workshops which were organized by the IEEE TC on Robot Learning:
- IROS 2012: Beyond Robot Grasping – Modern Approaches for Dynamic Manipulation
- AIMSA 2012: Advances in Robot Learning and Human-Robot Interaction
- ICRA 2010: Approaches to Sensorimotor Learning on Humanoid Robots
- R:SS 2009: Bridging the gap between high-level discrete representations and low-level continuous behaviors
- DAGSTUHL 2009: Cognition, Control and Learning for Robot Manipulation in Human Environments
- IROS 2008: Robotics Challenges for Machine Learning II
- NIPS 2007: Robotics Challenges for Machine Learning
Chairs of the Technical Committee
Cornell University, USA
University of Michigan, USA
Italian Institute of Technology, Italy
University of Tokyo, Japan
Technical Committee Website:
Special Issue on Humanoid Robotics
The “Advanced Robotics” journal is preparing a Special Issue on Humanoid Robotics.
SUBMISSION DEADLINE for papers: March 31, 2014
This is the official Call-for-Papers.
“Advanced Robotics” is the official international journal of the Robotics Society of Japan (RSJ).
More information about the journal here: http://www.rsj.or.jp/advanced_e/
I am co-editing this special issue, so I encourage everyone who considers submitting a paper to contact me well in advance before the deadline.
Special Issue on Humanoid Robotics
- Prof. Wataru Takano (The University of Tokyo, Japan)
- Prof. Tamim Asfour (Karlsruhe Institute of Technology, Germany)
- Dr. Petar Kormushev (Italian Institute of Technology, Italy)
SUBMISSION DEADLINE: March 31, 2014
Publication in Vol. 29, No. 5 (March 2015)
Humans understand the world through their actions upon the environment and their perception. The so-called anthropomorphism underlies this cognitive mechanism. Anthropomorphic robots, especially humanoid robots, can perform human-like actions, and enhance human viewers’ understanding of the intended effects of these actions. Humanoid robotics is a research area to pursue this capability from multiple viewpoints, such as body motion generation, motor skill learning, semantic perception, and to develop artificial systems able to communicate with humans. This research field has received significant attention in the last decades and will continue to play a central role in the robotics and cognitive systems research. This special issue will present the theoretical and technical achievements related to humanoid robotics, ranging from the mechanical design to artificial intelligence. Papers on all aspects of humanoid robots are welcome, including but not limited to, the following topics:
- Humanoid design
- Representation of humanoid robot motion
- Synthesizing human-like motions for humanoid robots
- Understanding intention of human actions
- Learning motor skills through imitation and reinforcement
- Control theory for humanoid behaviors
- Innovative sensing and actuation technologies applied to humanoid robots
- Modeling physical interaction between humans and humanoid robots
- Human-robot interfaces for skill transfer and communication
PDF format file of the full-length manuscript should be sent by March 31, 2014 to the office of Advanced Robotics, the Robotics Society of Japan through the homepage of Advanced Robotics (http://www.rsj.or.jp/advanced_e/submission). Sample form of the manuscript is available at the homepage.
Also, please send another copy to: Prof. W. Takano (takanoynl.t.u-tokyo.ac.jp), Prof. T. Asfour (asfourkit.edu), and Dr. P. Kormushev (petar.kormusheviit.it) for submission confirmation.
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