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    • was launched in July 2014, providing leading edge design engineering undergraduate and postgraduate education and research. The School offers a new four-year MEng undergraduate programme in Design Engineering, launched in October 2015, which represents a rigorous approach to design engineering, creativity, commerce and enterprise appropriate to 21st century industry. In addition the School offers the established two double-masters programmes in Innovation Design Engineering (IDE) and Global Innovation Design (GID), run jointly with the Royal College of Art.

      Applications are invited from individuals with a strong academic record (including a relevant PhD or equivalent) in a relevant engineering field (e.g. mechanical, electrical, software or control engineering), or a related field to robotics, computing, manufacturing, intelligent systems, industrial design, or innovation design engineering. Where relevant, experience in a multi- disciplinary context would be desirable. Applicants must have a track record of: high quality research, demonstrated by recent exceptional publications in internationally leading journals and conferences in robotics; and proven teaching excellence. Applicants are required to submit together with their applications their 4 best journal papers published since January 2010.

      Successful candidates will be expected to contribute to undergraduate and postgraduate teaching and to play a leading role in developing the School’s research in the relevant area, building on and extending the School’s current activities.

      Informal enquiries may be made to Dr Petar Kormushev (p.kormushev鸿运彩软件下载@imperial.ac.uk) and Prof. Peter Childs (p.childs鸿运彩软件下载@imperial.ac.uk) who is Head of the Dyson School of Design Engineering.

      Job details

      • Location: London, South Kensington
      • Salary: £57,020 per annum
      • Hours: Full Time
      • Contract Type: Permanent
      • Application deadline: 15th July 2016

      How to apply

      The preferred method of application is online via the website (please select “Job Search/Academic” then the job title or vacancy reference number, EN20160173AM). Please complete and upload an application form as directed.

      Further information is available at:

    • A competitive salary
    • Research and travel expenses of up to £45,000
    • Personal mentoring support from a senior Imperial academic
    • The chance to take full responsibility for setting and directing you鸿运彩软件下载r own research agenda

    Royal Society URF (University Research Fellowship)

    • 80% of the basic salary costs up to £39,389.64 in the first year, estates costs and indirect costs
    • Research expenses (up to £13,000 for the first year and up to £11,000 annually thereafter)

    RAEng Research Fellowship

    • Freedom to concentrate on basic research in any field of engineering
    • The services of a mentor to offer advice and to facilitate the formation of industrial links

    EPSRC Fellowships

    • EPSRC has defined three career stages (postdoctoral, early and established career) and the attributes expected at each stage.
    • Applications can be submitted at any time and will be processed on a rolling basis at a review panel.

    Newton International Fellowships

    • This scheme is for non-UK scientists who are at an early stage of their research career and wish to conduct research in the UK.
    • Eligibility requirements: to have a PhD, no more than 7 years of full-time postdoctoral experience, work outside the UK, and not hold UK citizenship

    .

    The available UROP projects are advertised by the corresponding supervisors here:

    Funding

    Students can apply to receive a bursary (funding) for the duration of their UROP project. The bursary will provide the student with a contribution towards their living costs for 6-12 weeks while undertaking a research experience within Imperial College during the summer of 2016.

    More information:

    Deadline

    The deadline to submit an application for funding is 14 March 2016.

    Supervision

    I am available to supervise undergraduate students for a UROP project on topics related to robotics and machine learning. Interested applicants should contact me by e-mail [p.kormushev (at) imperial.ac.uk].

    UROP project description (tentative)

    Title: Robotics and Machine Learning UROP
    Description: Depending on the skills and interests of the student, this UROP project could include designing a new robot, creating it using 3D printing, and controlling it. The main focus is on novelty – coming up with a novel robot design, or novel robot controller, or novel way to manufacture a robot, such as a robot arm or a mobile robot. In terms of software, the focus is on applying Machine Learning methods for the flexible control of a robot, and to allow the robot to learn new skills from experience. The topic is quite flexible and will be defined in collaboration with the student.
    Requirements: Basic knowledge of robotics, software programming skills, creativity.

    How to apply

    The scheme is now open for applications. Instructions for application:


    In close collaboration with
    Location: South Kensington campus, London, UK
    Start date: 1st May 2016 (or soon after)
    Duration: 3.5 years

    Closing Date: 10 April 2016

    Fully funded (all tuition fees paid) for UK/EU nationals, with additional stipend: 18,000 GBP per annum
    While this position is also open to Overseas applicants, they will only be funded up to the UK/EU level, and will be expected to provide self-funding for the remaining tuition fees.

    PhD Research Topic

    The foundations of robotics and robot control were established at a time when there was very limited computational power available. Therefore, the robots’ design and control algorithms were simplified to extreme. Nowadays, we have at our disposal huge computational resources, but we still continue building and controlling robots based on the old concepts. For example, the assumption that the robot links are rigid bodies and that the pose of the end-effector can be calculated through simple forward kinematics by measuring the joint angles is still standard. Such assumptions lead to bulky and heavy robots because the links must be designed not to bend during operation. Even series-elastic actuation relies on the same assumption of rigid links.

    The goal of this PhD research project is to investigate a radically new approach for controlling robots based on Machine Learning. Instead of using hand-made analytic models of a robot, the robot will learn its own model. Machine learning, including Deep Learning and Reinforcement Learning can be used to autonomously learn forward and inverse models of a robot’s kinematics and dynamics. Computer vision can be used to provide perception for both the environment and the robot’s own body. The ultimate goal would be the creation of a plug-and-play controller that works without any prior knowledge of the robot.

    Such a solution offers tremendous potential to revolutionize the way we design and control robots, and to significantly expand their capabilities. For example, the robot links will no longer need to be so stiff, and the kinematics will no longer need to be fixed. As an illustration, imagine a lightweight prosthetic arm or a robot exoskeleton that can grow, bend, and adapt to accommodate its patient. Such a device would be impossible to control with the existing control methods. Another example is flexible use of tools, where the robot easily adapts its controller to use any new tool by online learning of the combined arm-plus-tool kinodynamics. Further applications are envisioned to soft robots (e.g. elephant trunk like robots) which are difficult to control with conventional approaches.

    This research has the potential to lead to re-thinking of the established robot design paradigm (stiff links, fixed kinematics), since robot design and control are tightly coupled: the way we control robots determines the way we design them, and vice versa. Novel robot designs will be sought that leverage the rise of affordable 3D printing and novel smart materials, and could lead to the development of hybrid soft-hard robots, modular and reconfigurable robots (evolving hardware), self-repairing and self-improving robots, etc.

    690px-Dyson_logo.svg_small

    Funding

    The funding for this PhD position is provided by Dyson Ltd. Their focus is on forward-looking research in robot perception and control with the goal of developing the breakthrough technology which will lie at the heart of new categories of robotic products for the 鸿运彩软件下载 and beyond. Potential applications for the developed research will be sought in close collaboration with Dyson’s Robotics Research group.

    Supervision

    The PhD student will be supervised by Dr Petar Kormushev at the Dyson School of Design Engineering, with possible co-supervision from the Dyson Robotics Lab at Imperial’s Department of Computing.

    Workplace

    The Dyson School of Design Engineering is the 10th and newest engineering department at Imperial College London. It was formed in July 2014, building on the long-standing design and engineering expertise at Imperial as well as the world-renowned Innovation Design Engineering (IDE) programme run jointly by Imperial and the Royal College of Art. The School has a fast growing population of both staff and students. It is located at the South Kensington campus of Imperial, right next to Hyde Park.

    Requirements

    – You must have an MEng or MSc degree (or equivalent experience and/or qualifications) in an area pertinent to the subject area, i.e. Computing, Mathematics or Engineering.
    – You must have a high standard undergraduate degree at UK 1st class or 2:1 level (or international equivalent)
    – You must be fluent in spoken and written English and meet Imperial’s English standards.
    – You must have excellent communication skills and be able to organise you鸿运彩软件下载r own work and prioritise work to meet deadlines.
    – The ideal candidate will have strong background in both Machine Learning and Robotics.
    – Strong academic track record and practical software skills are desired.
    – Any published scientific papers would be a plus.

    How To Apply

    All applications must be sent to Dr Petar Kormushev (p.kormushev [at] imperial.ac.uk) with the keyword “[PhD-2016-Imperial-Dyson]” in the subject field.

    Applications must include the following:
    – Full CV, with a list of any significant course projects and/or industrial experience;
    – A 2-page research statement indicating what you鸿运彩软件下载 see are interesting research issues relating to the above PhD topic description and why you鸿运彩软件下载r expertise is relevant;
    – Full academic transcripts/grades;
    – A copy of all publications of the applicant (if any).

    Selected applicants will be encouraged to submit a formal application online at:

    For any questions regarding the application process please contact Dr Petar Kormushev (p.kormushev [at] imperial.ac.uk).


    Dr Petar Kormushev
    Lecturer in Robotics and Computing

    Dyson School of Design Engineering
    Imperial College London

    South Kensington, London, SW7 2AZ
    Work phone: +44-20-75949235




    My new position will be Lecturer in Robotics and Computing at the .

    This is my .

    I will also continue supervising PhD students at the   which I was leading until now at the Italian Institute of Technology (IIT).

    Our robot is called WALK-MAN, and is representing Italy:
    http:///topics/walk-man-robot/

     

    Dr. Petar Kormushev shows the capabilities of the state-of-the-art robots at the Italian Institute of Technology.

    Sofia_Science_Festival_2014_Petar_Kormushev_title_640px

    The demonstrations include various methods for machine learning that allow the robots to learn useful new skills.

    Dr. Kormushev was awarded with the John Atanasoff award in 2013 by the President of Bulgaria.

     

    More information – Italian institute of technology:
    http://www.iit.it/

     

    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.




    Advanced_Robotics_logo_JP

    Special Issue on Humanoid Robotics

    Guest Editors:

    • 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   April 14, 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

    Submission:
    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 鸿运彩软件下载page of Advanced Robotics (). Sample form of the manuscript is available at the 鸿运彩软件下载page.

    Also, please send another copy to: Prof. W. Takano (takano(a)ynl.t.u-tokyo.ac.jp), Prof. T. Asfour (asfour(a)kit.edu), and Dr. P. Kormushev (petar.kormushev(a)iit.it) for submission confirmation.

    Advanced_Robotics_background_crop

    People will turn partially into 鸿运彩软件下载

    Sorry, this entry is only available in Български.

    I received the 2013 John Atanasoff award

    I was awarded by the President of Bulgaria with the prestigious John Atanasoff award in 2013.


    The award is named after Prof. John Vincent Atanasoff, an American physicist of Bulgarian descent who was the inventor of the first electronic digital computer ABC.

    The 33-year-old scientist in the area of information technology, Dr. Petar Kormushev, became the holder of the 2013 John Atanasoff аward. Petar Kormushev has been nominated for the award for his work in robotics, machine learning, and artificial intelligence. The distinction was given to him by the President of Bulgaria, Mr. Rosen Plevneliev, at a ceremony in Sofia on October 4th, 2013. Other you鸿运彩软件下载ng scientists were singled out with diplomas.

    Photos from the award ceremony



    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 ).

    The project is a collaboration of five universities and institutes in Europe: Heriot Watt University (UK), Italian Institute of Technology (Italy), University of Girona (Spain), King’s College London (UK), and National Technical University of Athens (Greece).

    The accepted candidate will contribute to the development and experimental validation of novel reinforcement learning and imitation learning algorithms for specific application to robot control of autonomous underwater vehicles.

    The research work includes conducting experiment with AUVs in water tanks in collaboration with the other project partners. The developed machine learning algorithms will also be applied for other robots available at IIT, such as the compliant humanoid robot COMAN, the humanoid robot iCub, Barrett WAM manipulator arm, and KUKA LWR arm robot.

    The research will be conducted within the “Learning and Interaction Group” () with team leaders: Dr. Petar Kormushev and Dr. Sylvain Calinon.

    The salary will depend on the candidate’s experience. Policies provide additional pension and health benefits. Applicants may also qualify for reduced taxes benefits. Contracts will be for the duration of the project. Expected starting date is as soon as possible.

    International applications are encouraged and will receive logistic support with visa issues. For further information please contact: Dr. Petar Kormushev (petar.kormushev AT iit.it).

    APPLICATION DEADLINE: June 29, 2012

    The official job posting on the IIT website can be found here:

    is a movement started by mathematicians and other academics who are protesting against the business model of the big publishers like Elsevier, Springer, Wiley, and etc.

     

    Currently, the academics are set to boycott the Elsevier’s business practices, as explained in this

     

    ) at the Italian Institute of Technology (IIT, an English-language research institute, located in Genoa, Italy) has 2 Post-Doc openings (starting from January March 2012) in the research areas of Reinforcement learning and Imitation learning applied to robot control of Autonomous Underwater Vehicles (AUV).

    The successful candidates will participate in a 3-year research project funded by the European Commission under the Seventh Framework Programme (FP7-ICT, STREP, Cognitive Systems and Robotics) called “PANDORA” (Persistent Autonomy through learNing, aDaptation, Observation and ReplAnning) which will start in January 2012.

    The project is a collaboration of five universities and institutes in Europe: Heriot Watt University (UK), Italian Institute of Technology (Italy), University of Girona (Spain), University of Strathclyde (UK), and National Technical University of Athens (Greece).

    The accepted candidates will contribute to the development and experimental validation of novel reinforcement learning and imitation learning algorithms for specific application to robot control of autonomous underwater vehicles. The research work includes conducting experiment with AUVs in water tanks in collaboration with the other project partners. The developed machine learning algorithms will also be applied for other robots available at IIT, such as the compliant humanoid robot COMAN, the humanoid robot iCub, Barrett WAM manipulator arm, and KUKA LWR arm robot.

    The research will be conducted within the “Learning and Interaction Group” ()
    with team leaders: Dr. Petar Kormushev and Dr. Sylvain Calinon.

    The salary will depend on the candidate’s experience and also includes additional pension and health benefits. Applicants may also qualify for reduced taxes benefits. Contracts are for up to 3 years with a possible renewal and future career options upon successful completion. Expected start date is February March 2012.

    International applications are encouraged and will receive logistic support with visa issues. For further information please contact: Dr. Petar Kormushev (by e-mail).

    Application Requirements:

    – PhD degree in Computer Science, Mathematics or Engineering
    – High-quality publication record
    – Strong interest in machine learning algorithms
    – Strong competencies in some of these areas: machine learning, reinforcement learning, imitation learning, MATLAB and C/C++ programming
    – Experience in robot control is a plus
    – Fluency in both spoken and written English

    Application Procedure:

    To apply please send a detailed CV, a statement of motivation, degree certificates, grade of transcripts, contact information of at least two references, and other support materials such as reference letters to: Dr. Petar Kormushev (by e-mail).

    For consideration, please apply by:  December 4, 2011
    DEADLINE EXTENDED TO: January 29, 2012

    Petar Kormushev, PhD
    Team Leader – Advanced Robotics Dept.
    Italian Institute of Technology (IIT)
    Via Morego 30, 16163 Genova

     

     


     

    Doctoral Course on Robotics, Cognition and Interaction Technologies
    Call for PhD students for 2012


    30 open PhD positions with scholarship are available at the Italian Institute of Technology (IIT) in Genoa, Italy.
    Doctoral course starting in January 2012
    Application deadline: September 23, 2011

     

    I have 2 PhD openings in my group, in the field of Reinforcement Learning with application to Robot Control. You can find details in this PDF document.
    The 2 PhD positions under my supervision are in:

     

    STREAM 3: Machine Learning, Robot Control and Human- Robot Interaction

    • Theme 2.7: Machine learning for robot control of autonomous underwater vehicles
      Tutor: Dr. Petar Kormushev, Dr. Sylvain Calinon, Prof. Darwin G. Caldwell
      Number of available positions: 1
    • Theme 2.8: Machine learning for a soft robotic arm assisting in minimally invasive surgery
      Tutor: Dr. Petar Kormushev, Dr. Sylvain Calinon, Prof. Darwin G. Caldwell
      Number of available positions: 1

     

    For further details about these particular PhD positions, please contact me by e-mail.

    Pizza robot 鸿运彩软件下载@ AAAI 2011


    At the international conference AAAI 2011 in San Francisco, my colleague Sylvain and I presented our pizza-making robot.

    The event was the so-called “Robotic Challenge 鸿运彩软件下载@ AAAI”, and this year the topic was “Food preparation”.


    Our robot is a modified Barrett WAM 7-dof robot arm manipulator, with a wooden rolling pin at the end-effector.

    The robot learns from demonstrations how to roll out the pizza dough, in order to make the most perfect circular pizzas! Below you鸿运彩软件下载 can see a video of the Robotic Challenge event, and here are a few photos of our setup:






    Learning from Demonstration Robotics Challenge 鸿运彩软件下载@ AAAI 2011
    Video credit: Brandon Rohrer