RIPS Tornemo Mexicano de Robotica 2012
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Transcript of RIPS Tornemo Mexicano de Robotica 2012
HARDWARE
SOFTWARE
The robot Golem-II+ is the latest service robot developed by the Golem Group.
We design and construct domain independent service robots based on a theory of Human-Robot Communication centered in the interaction context, and the specification of Speech Acts protocols, which are named Dialogue Models (DMs).
IOCA
- PeopleBot robotic base - Dell Precision M4600 - QuickCam Pro 9000 Webcam - Microsoft Kinect Camera x2 - Hokuyo UTM-30LX Laser - Shure Base Omnidirectional microphones x3 - RODE VideoMic directional microphone - M-Audio Fast Track Ultra external sound interface - Infinity 3.5-Inch Two-Way loudspeakers x2 - LAIDETEC-IIMAS robotic arm x2
DMs are embedded in an Interaction-Oriented Cognitive Architecture (IOCA) which coordinates perceptual and motor actions within the main communication cycle. IOCA also includes a set of reactive behaviors that allow the robot to respond directly, and a coordinator, which permits that reactive behavior and inferential processes proceed smoothly in a coordinated fashion. DMs and IOCA permit to model structured and multimodal conversations between people and service robots in diverse application domains. DMs are also defined and manipulated independently of IOCA's modules which remain fixed among different application domains and tasks.
GOLEM-II+
Departamento de Ciencias de la Computación
GOLEM-II+The Golem Group
Computer Science DepartmentInstituto de Investigaciones en Matemáticas Aplicadas y en Sistemas
Universidad Nacional Autónoma de México
http://[email protected]
IOCA
InterpretationsExpectationsAction Protocols
Modal Codifications
Concrete Actions
EXTERNAL REPRESENTATIONS OR THE WORLD
RenderingDevices
Specification Module
Coordinator
Dialogue Manager
Semantic Memory
Interpretation Module
RecognitionDevices
AutonomousReactive Systems
IOCAPerceptual Memory
A full DM can be embedded within a situation. Situations, Expectations and Actions can be defined parametrically as functions of the interaction context. The next situation is determined by the current interpretation and also by the task history.
During task execution the robot performs the action that is best met in the situation. In case there is no expectation satisfied by the world, the robot is "out of context" and performs a recovery protocol to place itself in context again and establish the common ground.
TEAM MEMBERS
Luis Pineda (team leader), Ivan Meza, Caleb Rascón, Gibran Fuentes, Carlos Gershenson, Mario Peña, Iván Sánchez, Mauricio Reyes, Hernando Ortega, Arturo Rodríguez, Lisset Salinas, Joel Durán, Esther Venegas, Varinia Estrada
DIALOGUE MODELS
DMs are information states named "situations", which are defined in terms of expectation and action pairs (E:A). A different set of expectations determines a different situation.
Subordinate Dialogue Model Temporal Occlusion
Si
cstart:hello
ε:start_button
Main Dialogue Model - Follow Me Test
Ricontinue:ε
Rot Rrl Rrucontinue:ε
continue:εcontinue:ε
Rlm
fs
finish:goodbye
si
v1
n
see(N):see_you
ε:ε
v2
Rb
no_detect:dont_see_you
fs continue
stop_gesture(N):dont_move
see(N):see_you_againocclusion(N):wait
occlusion(N):something_between
ε:ask_for_help
SOFTWARE LIBRARIES
JACK, PocketSphinx
OpenCV, OpenNI, MOPED
Sicstus Prolog
Festival TTS
Player/Stage and Gearbox
MODULE
Navigation
Dialogue Manager
Vision
Voice Recognition
Voice Synthesizer
Object Manipulation Roboplus
WordSpotting, GF grammarLanguage Interpretation
ABILITIES
PERCEPTION AND ACTION FUNCTIONALITY
Robot locates the third party by the source of sound with a percep-tual scheme, rotates and face him to attend the interruption.
DISTINCTIVE FUNCTIONALITY: ORIENTATION BY SOURCE OF SOUND
I'm attending someone else. Please, wait. I'll be with
you in a minute.
Please, wait
Bring me the juice
Hi, Golem!
¿? Ok. Thanks!
Sorry! You said juice, right?
Yes, please.
Robot and user are engaged in a task oriented conversation. A third party interrupts taking the conversatio-nal initiative.
Robot records the parameters of the inte-rruption, accomplishes the original task and returnes to the third party.
NAVIGATION
VISION
AUDIOLOCALIZATIONOBJECT MANIPULATION
Robotic orientation towards speaker using 3 microphones
Image Triangle Array-Redundancy
OBJECT RECOGNITION
Object Model Recognized Object
FACE RECOGNITION
Examples of eigenfaces
PEOPLE TRACKING AND GESTURE RECOGNITION
+ 4 degrees of freedom+ Reach: 10-90cm+ Hands with sensors + Openning to 30cm+ Load: 500gr