02/06/2020
The Human Resources Strategy for Researchers

PhD contract in the field of Computer science financed during 3 years by the University Clermont Auvergne

This job offer has expired


  • ORGANISATION/COMPANY
    Université Clermont Auvergne
  • RESEARCH FIELD
    Computer science
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    28/06/2020 00:00 - Europe/Brussels
  • LOCATION
    France › AUBIERE
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35 H
  • OFFER STARTING DATE
    01/10/2020
  • REFERENCE NUMBER
    UCA/ANR/007
  • IS THE JOB RELATED TO STAFF POSITION WITHIN A RESEARCH INFRASTRUCTURE?
    Yes

Supervisor: Youcef Mezouar (IP) / Olivier Stasse (LAAS)

Laboratory: Institut Pascal (IP), LAAS

Email and phone: youcef.mezouar@sigma-clermont.fr

+33(0) 473 288 065

Co-advisor(s): Sébastien Lengagne (IP)

Abstract (up to 10 lines):

Learning methods have proven to be effective in image processing but

their application to robotic applications remains difficult, mainly

because of the learning times. The transfer of a skill acquired by one

robot to another robot can reduce the teaching time. The objective of

the thesis is to continue the work on the transfer of skills between

robots by studying an abstract and universal representation of the

state and actions of the robot.

Skills:

autonomous, curious and persevering. Knowledge in programming

(C++/Python), Robotics and Artificial Intelligence.

Keywords:

Robotics, neural network, skill transfer, control, state abstraction

Description (up to 1 page):

Teaching methods have proven their effectiveness in image

processing and are beginning to be applied for robot control.

Unfortunately, these methods require, for each robot and for each

task, a very long training time in simulation or in real life as well as

expertise to set the teaching parameters. The objective is to keep

these training times as short as possible by transferring the

competence related to a task from one robot to one or more other

robots on the same task. Recent work in the laboratory introduces a

new neural network architecture that decorates the robot and task

information. They show that it is possible to learn a task with a robot

and to transfer this skill to a robot with a different mechanical

structure (number of joints, body length). This network is based

internally on a heuristically defined representation of the robot state

and the task. The contribution of this thesis will be in the continuity of

recent works by finding the best abstraction of the state of the robot

and of the task, as well as to propose a teaching process adapted to

this type of network. The long term goal will be to allow a transfer of

skills from one robot to another (or from a simulation to the robot)

without the need for an adaptation phase.

Références (up to ½ page):

M. Mounsif and S. Lengagne and B. Thuilot and L. Adouane

Universal Notice Network: Transferable Knowledge Among Agents

IEEE - 6th 2019 International Conference on Control, Decision and

Information Technologies (IEEE-CoDIT 2019), Apr 23-26, 2019, Paris -

France

Mehdi Mounsif, Sébastien Lengagne, Benoit Thuilot, Lounis ADOUANE

BAM! Base Abstracted Modeling with Universal Notice Network: Fast

Skill Transfer Between Mobile Manipulators

IEEE - 7th 2020 International Conference on Control, Decision and

Information Technologies (IEEE-CoDIT 2020)

How to candidate?

Contact : sebastien.lengagne@uca.fr,

youcef.mezouar@sigma-clermont.fr.

 

 
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Benefits

 

 
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Eligibility criteria

 
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Selection process

 

 
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Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Other: Master Degree or equivalent

Skills/Qualifications

 

 
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Specific Requirements

 

 
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Work location(s)
1 position(s) available at
Pascal Institute (IP)
France
Région Auvergne Rhône-Alpes
AUBIERE
63178
Campus Universitaire des Cézeaux TSA 60026 CS 60026 4, Avenue Blaise Pascal

Open, Transparent, Merit based Recruitment procedures of Researchers (OTM-R)

Know more about it at Université Clermont Auvergne

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EURAXESS offer ID: 528422

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