COACHES ART-ADN Le numérique au service du handicap Travaux du laboratoire GREYC - Organisé par le CCAS - la Ville de Caen - le Dôme
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Le numérique au service du handicap
Travaux du laboratoire GREYC
COACHES
ART-ADN
Organisé par le CCAS – la Ville de Caen – le Dôme
CHIST-
ERA/2014
COACHES
COoperative Autonomous Robots in
Complex and Humans EnvironmentsS
Coordinateur : Abdel-Illah Mouaddib
Partenaires :Unicaen (F), U.Sapienza (I), U. Vreije (B), U. Sebanci (T)
Motivation
Deploying robots in public area to assist, guide, and escort visitors
and surveillance
Visual applications are born:
Guidance and Personal assistance in public area
Shop malls, touristic sites, airport, train stations, hospitals
Surveillance and patrolling in cooperative way with intervention
units (firefighters, police, medical units, and tourist office staff, …)
Our target use cases:
Caen Rive de l’orne MALL in cooperation with Caen city
COACHES
OBJECTIVES OF THE PROJECT
Public spaces in large cities are increasingly Assis ng Surveilling Informing
Services
Manager or
becoming complex and unwelcoming Guiding
People Monitoring
the environment
Shopkeepers
environments. COACHES project addresses
Sensor! Seman8c! Knowledge! Ac8ons! Sensor! Seman8c! Knowledge! Ac8ons!
Processing! Interpreta8on! Update! Processing! Interpreta8on! Update!
! !
Sensor! Seman8c! Knowledge! Ac8ons!
Software
network! network!
KB! ! KB! !
! ! Processing! Interpreta8on! Update! ! !
! ! !
! !
Scene!Analysis!and!understanding!(WP2)!
!
Knowledge>based!environment!!
network! ! !
Scene!Analysis!and!understanding!(WP2)!
!
Knowledge>based!environment!!
! KB! ! !
! !
modelling!!and!reasoning!(WP1)! Mul= >robot! ! ! ! !
modelling!!and!reasoning!(WP1)! Mul= >robot!
T21! coopera=
! ve! ! T21! coopera=
! ve!
!
T22!
! planning!under! ! !
Scene!Analysis!and!understanding!(WP2)!
!
Knowledge>based!environment!!
!
T22!
! planning!under!
RealB8me!image! RealB8me!image!
S! and!video!
Situa8on!
!
awareness
! !
uncertainty!(WP4)!
!
! !
modelling!!and!reasoning!(WP1)!
!
Mul= >robot! S! and!video!
Situa8on!
!
awareness
! !
uncertainty!(WP4)!
!
processing! T21! coopera= ve! processing!
E!! ! ! ! T42!
!
T22!
!
!
planning!under!
E!! ! ! ! T42!
N! T11!
T12!
! Mul8Brobot! A! S! RealB8me!image!
Situa8on! uncertainty!(WP4)!
!
N! T11!
T12!
! Mul8Brobot! A!
! ! coopera8ve! and!video! !
awareness
! ! ! ! coopera8ve!
S! Mul= >modal!short>term!human>robot! KnowledgeB
Spa8al,!common!
! planning! C!! E!! processing!
! ! T42!
S! Mul= >modal!short>term!human>robot! KnowledgeB
Spa8al,!common!
! planning! C!!
! ! sense!and!!non! ! ! ! sense!and!!non!
fundamental issues related to the design of a
based! based!
O!
interac= on(WP3)!
environment!
monotonic! T! N! T11!
T12!
! Mul8Brobot! A! O!
interac= on(WP3)!
environment!
monotonic! T!
! !
modelling!and!
reasoning! !
! ! coopera8ve! ! !
modelling!and!
reasoning! !
R! Seman8c!maps! U! S! Mul= >modal!short>term!human>robot! KnowledgeB
Spa8al,!common!
! planning! C!! R! Seman8 c!maps! U!
! ! !
T41! interac= on(WP3)! ! !
based! sense!and!!non!
! ! !
T41!
S!
T31! T32!
A! O! environment!
monotonic!
! T! S!
T31! T32!
A!
! ! ! Robust! ! !
modelling!and!
reasoning!
! ! ! Robust!
Mul8Bmodal! Human!needs!
naviga8on T! R! Seman8c!maps! ! U! Mul8Bmodal! Human!needs!
naviga8 on T!
shortBterm!HRI es8ma8on
! ! ! ! T41!
shortBterm!HRI es8ma8on
! !
O! S!
T31! T32!
!
A! O!
! ! Mul8Bmodal! !
Human!needs! ! Robust! ! !
R! shortBterm!HRI es8ma8 on
naviga8on T! R!
! Shopkeepers! ! ! ! Shopkeepers!
S! O! S!
Visitors! Managers! ! ! Visitors! Managers!
R!
! Shopkeepers!
Managers!
S!
Visitors!
robust system of self-directed autonomous
robots with high-level skills of environment
modeling and scene understanding, distributed
Robots
autonomous decision-making, short-term
interacting with humans and robust and safe
navigation in overcrowding spaces.
Sensor Seman c Knowledge Ac ons
Processing Interpreta on Update
network
KB
Scene Analysis and understanding (WP2) Knowledge-based environment
modelling and reasoning (WP1) Mul -robot
T21
T22
coopera ve
ROBOT-1 Goals Gi* accomplished Goal G* of the robot planning under
Real- me sensor,
WP2: Percep on by the other robots sent to the other robots S image and video
Situa on
awareness
uncertainty (WP4)
processing
GOALS
π E T42
KB Message of the A
DEC EXEC N T11
T12 Mul -robot
Extracted features end of the goal G* coopera ve
S Mul -modal short-term human-robot Knowledge-
Spa al, common
sense and non
planning C
interac on(WP3) based
O monotonic T
PERRCEPTION WP2:
WP2 KB environment
reasoning
External Cameras
WP1 modelling and
ROBOT-2 Goal G* selected R Seman c maps U
NETWORK
KB reasoning
PRUs-task Library by the robot T31 T32
T41
A
GOALS S Robust
Informa on π List of goals
Mul -modal Human needs
naviga on T
KB DEC EXEC
short-term HRI es ma on
Generated O
WP4 at me t: Gt R
MDP-based planning DECISION Shopkeepers
List of goals Selected PRU Managers
S
Visitors
ROBOT-3
Computed policy π π(G*) policy
GOALS π
KB DEC EXEC
Petri-Net execu on plan EXEC
Naviga on Assistant
!
SERVICES Advertising Assisting Escorting Support for security
Assistance des personnes avec des capacités limitées Défintion de nouvelles modalités d’interaction avec des limitations de la vue de l’ouie de la parole
Nouvelles modalités d’interaction
Vision robotique robuste
Reconnaissance de gestes et
langage des signes
Reconnaissane de l’émotion
Capteurs de forces
Une lesse et capteurs de
contact
Synthèse de la parole
Système de reconnaissance des comportements
La gestuelle et l’émotion Geste Emotion
Fabrice Maurel – Université de Caen Normandie
– Laboratoire GREYC équipe HUman Language
TECHnology (HULTECH)
IHM : TAL :
Interactions Traitement
Homme Automatique
Machine des LanguesAccès non visuel aux pages Web
Accès non visuel aux interfaces tactiles (VoiceOver – Talkback…)
Stratégies de lecture non visuelle de haut niveau
Skimming non visuel : Scanning non visuel :
On crée des paysages ! On crée des chemins !
Approches orientées
« texte » (Oral/Braille) :
On traduit !
Approches orientées
« image » (Tactile) :
On transpose !Deux projets
ZONE 1
ZONE 2
ZONE 3
ZONE 4
en cours
ZONE 6
ZONE 7
ZONE 8
ZONE 5
ZONE
9
Menu haut 1 Vidéo
CAC 40 Menu haut 2 Les plus
partagés
Couac trains Nous suivre
régionaux Éditions abonnésTACTINET : premiers résultats
Etudes perceptives et de
reproduction de formesMétaphore de l’effet « cocktail party » TAGTHUNDER : première approche
https://tagthunder.greyc.fr/demo/ TAGTHUNDER : première réalisation
TAGTHUNDER :
premiers
résultats
• Utilisateurs voyants
• Expérience ressentie comme difficile
• Très peu d‘erreursMerci de votre attention
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