20/07/2018

Scene Understanding and Movement-based Human-Robot Collaboration in Industry 4.0

This job offer has expired


  • ORGANISATION/COMPANY
    MINES ParisTech - Centre for Robotics
  • RESEARCH FIELD
    Computer science
    EngineeringElectrical engineering
    MathematicsApplied mathematics
  • RESEARCHER PROFILE
    Recognised Researcher (R2)
    Established Researcher (R3)
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    15/05/2019 05:00 - Europe/Brussels
  • LOCATION
    France › Paris
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    37
  • OFFER STARTING DATE
    01/06/2019
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020
  • REFERENCE NUMBER
    820767

Introduction:

The Centre for Robotics of MINES ParisTech, PSL Université Paris, is involved in several research projects on human motion pattern recognition applied to the Factory of the Future, the Creative and Cultural Industries and the Autonomous Vehicles. The main objective of these projects is the development of novel methodologies and technological paradigms that improve the perception of the machine and allows for natural body interactions in human-machine partnerships.

Topic:

MINES ParisTech is opening a position on Scene Understanding and Movement-based Human-Robot Collaboration (HRC) in Industry 4.0 in the context of the H2020 Collaborate project. HRC requires a smooth, natural and efficient coordination between robots and human operators. During collaborative tasks, it is crucial to establish a safe framework for the human worker by improving the robot’s perception. The machine, whether a Humanoid Robot or an AGV, must be able to detect: 1/ not only the human presence (e.g. operator or visitor) but also 2/ specific actions/intentions and/or gestures. The operators perform these gestures in production lines (e.g. to screw, to assembly, etc.) or generally in space (e.g. when a human tends to cut the motion trajectory of the AGV or is giving to it basic gestural commands, e.g. to charge or not a palette, to go back to the starting point, etc.). To achieve this goal, the candidate will develop tools and methods for both scene understanding and human tracking by using OpenPose and TensorFlow, whether the camera is fixed (e.g. on a Humanoid Robot) or in motion (e.g. on an AGV). With regards to the scene analysis, deep and machine learning will be used in order to extract meaningful features from RGB-D sensing (e.g. Random Decision Forests, Geodesic distances etc.) and segment the scene into objects, workbench etc.. Moreover, the tools of the worker will be augmented by using inertial sensors and detect whether they are used or not, when needed. For the gesture/action recognition itself, it shall be based on spatial trajectories of tracked joints and other time-series. Since the ultimate goal of this research is a safe Human-Robot Collaboration framework, early recognition and prediction techniques will be used, such as Hidden Markov Models, Gaussian Mixture Models, Deep Learning, etc. In particular, the use of time-series specific methods of Deep-Learning, recently proposed by the Centre for Robotics, shall be investigated. The candidate will deliver a generic methodology and a technological prototype for professional gesture and intentions recognition, which will be tested in 4 use-cases: a. car starter assembly, b. windshield visual quality control, c. LCD TV assembly and d. aircrafts parts manufacturing.

This position will give the possibility to the candidate to work with other European researchers both in the project and in the wider academic community, as well as opportunities to work directly with industrial partners. Moreover, the candidate will acquire transferable skills that will enhance future employability through leading and contributing to highly interactive and collaborative work. Finally, the candidate will be autonomous and concentrated on his/her work and will contribute to the project management tasks, such as preparation of the project meetings (distance calls or physical meetings in different European countries – 3 per year), reports and deliverables. Active assistance in the teaching duties of the Post-Master’s Degree AIMove is also expected.

Benefits

The candidate researcher will have a 12-month contract, extendable up to 24 months (depending on the profile of the candidate and the requirements of the project). The gross monthly salary will depend on the profile/experience of the candidate. Complementary activities to research, such as teaching or providing reports and deliverables, etc., are included into the salary.

Eligibility criteria

Completed five years of studies and have received a Master or a PhD.

Additional comments

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Computer science: Master Degree or equivalent
    Engineering: Master Degree or equivalent
    Mathematics: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

We are looking for a motivated and talented young researcher (Postdoc or Engineer) who has completed at least five years of studies or has received a Master Degree, or a Phd, in one of the following domains:

  • Machine or Deep Learning
  • Human Pose Detection
  • Computer Vision
  • Pattern or Gesture Recognition
  • any relevant domain

Specific Requirements

The candidate researcher should have excellent skills on:

  • Machine and/or Deep Learning
  • Signal Processing
  • Parallel programming in GPUs: C++, Python, R.

Moreover, the young researcher must be proficient in both written and spoken English and possess excellent presentation and communication skills which will be needed for regular interactions with the project partners (e.g. industrial partners, coordinator, engineers workers, etc..). Good knowledge of French would be appreciated. Furthermore, any type of experience in EU collaborative projects would be useful.

Work location(s)
1 position(s) available at
MINES ParisTech
France
Paris
75006
60, Boulevard Saint-Michel

EURAXESS offer ID: 326208

Disclaimer:

The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.

 

Please contact support@euraxess.org if you wish to download all jobs in XML.