Master internship position to fill with a possible extension
to a PhD thesis
Title: Multimodal merging for social robots
Keywords: Multimodal merging, neural fields, active
perception, developmental learning, social robotics, dynamical
systems.
Subject:
To have a consistent perception of its surrounding world, an agent
has to continuously merge the data flows coming from its various
sensors. Multiple studies were done in animals and humans to
understand this process at the neuronal and behavioral levels [5].
Especially, it looks like humans are able to merge data in a
statistically optimal fashion [2].
Through this internship, the selected candidate will participate in
the AMPLIFIER project that targets to study how an artificial agent
can autonomously learn to merge multiple data sources and especially
how it can attribute the right relevance to each source, with
respect to the precision of the sensors, the current stimulus, the
task, … Our hypothesis is that active perception (i.e. active
sampling of data in the environment, e.g. by moving the eyes to
sample visual data) plays a key role in this process. We want to
test it in psychophysics experiments and explore how it can improve
human-robot interactions.
More precisely, the intern will study how to integrate the relevance
of modalities in the neural field paradigm [1] that was previously
used for multimodal merging [3]. On one hand, this work will be used
for modeling psychophysical results (performed by other members of
the project). On the other hand, it will be coupled with previous
work on active perception and anticipation learning [4]. This raises
research questions on multimodal attention that will be studied
during this internship.
The AMPLIFIER project (2018-2022) includes members from Lyon 1
University (LIRIS, CRNL), Univ. Grenoble Alpes (LJK, Gipsa-lab,
LPNC) and Hoomano, a start-up located in Lyon. The intern will thus
have to interact with multiple collaborators (academic and firm
researchers, engineers) from multiple domains (computer science,
psychophysics, statistics, computational neuroscience, robotics).
Pro file:
Ideally, the candidate would have the following skills:
– studies in artificial intelligence / machine learning /
computational neuroscience (or equivalent)
– good programming skills (Python, git)
– autonomy
– ability to work in a team
– scientific curiosity
– good written/oral English skills
Any of these skills will be a plus:
– programming skills in web technologies
– previous experience with robots (especially Nao and Pepper)
– interest/knowledge in neuroscience and/or psychophysics
– previous experience in research
Localization:
LIRIS laboratory, Lyon, France.
The intern may occasionally have to go in the Hoomano office in Lyon
or LJK laboratory in Grenoble.
Duration:
The internship will begin in February-April (starting date subject
to negotiation) for 5 months.
This internship can lead to a 3 years PhD thesis (funding provided
by the AMPLIFIER project) that will be co-directed between
Grenoble and Lyon with time shared between both sites.
Gratification:
3.6€/h, 35h/week (i.e. around 520€/month)
Advisors:
Mathieu Lefort: associate professor at SMA group, LIRIS
laboratory, Lyon
Jean-Charles Quinton: associate professor at SVH team, LJK
laboratory, Grenoble
Application:
To apply, please send a CV and application letter to Mathieu
Lefort (mathieu.lefort ‘at’ liris.cnrs.fr) and Jean-Charles
Quinton (jean-charles.quinton ‘at’ imag.fr). The applications will
be processed on the fly until the position is filled.
If you have any question regarding this internship position,
please send a mail to Mathieu Lefort.
References:
[1] Shun-ichi Amari. Dynamics of pattern formation in
lateral-inhibition type neural fields. Biological cybernetics,
27(2) :7787, 1977.
[2] Marc O Ernst and Martin S Banks. Humans integrate visual and
haptic information in a statistically optimal fashion. Nature,
415(6870) :429433, 2002.
[3] Mathieu Lefort, Yann Boniface, and Bernard Girau. Somma :
Cortically inspired paradigms for multimodal processing. In IJCCN
2013, pages 18. IEEE, 2013.
[4] Jean-Charles Quinton, Nicola Catenacci Volpi, Laura Barca, and
Giovanni Pezzulo. The cat is on the mat. Or is it a dog ? Dynamic
competition in perceptual decision making. IEEE
Transactions on Systems, Man, and Cybernetics : Systems, 44(5)
:539551, 2014.
[5] Barry E Stein and M Alex Meredith. The merging of the senses.
The MIT Press, 1993.
—
LEFORT Mathieu