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Markovito’s Team (INAOE, Puebla, Mexico). Team members. Sabina : hardware platform. PeopleBot Laser SICK LMS200 PTZ system - video camera VCC5 Two rings of sonars and infrared sensors Stereo vision (videre) Directional microphone and speakers Gripper 2 D.O.F and bumpers. Map building. - PowerPoint PPT Presentation
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Markovito’s Team(INAOE, Puebla, Mexico)
Team members
Sabina: hardware platform
• PeopleBot • Laser SICK LMS200• PTZ system - video
camera VCC5• Two rings of sonars
and infrared sensors• Stereo vision (videre)• Directional microphone
and speakers• Gripper 2 D.O.F and
bumpers
Map building
The initial map is built integrating laser and sonar scannerswith particle filters, represented as a probabilistic grid
Visual features (SIFT) are integratedto the map for improving localization
Navigation and Localization
Global and local localization is based on natural landmarks:corners and walls (laser), and SIFT (vision)
My flexible and robust navigation algorithm combines an initial plan based on PRMs with a reactive navigator that uses TOPs learned from examples
Face recognition
Localization and tracking
SIFT feature extraction
Face recognition
Video streaming
Results
Identification based on silhouettes
People identification uses stereo vision and is based on distance and silhouettes models
Can identify people standing or sitting, facing forward or seen from the side
Voice recognition, synthesis and animated face
Speech synthesis and recognition uses standard tools combined with text processing, directed by the coordinator according to the task
My animated face can express different emotions and it is synchronized with my speech
Object Manipuation
Rapidly Exploring random trees were implemented for motion planning in order to reach a grasping configuration.
The Katana arm provides to Sabina with object manipulation capabilities
Coordinator - MDP
The coordination of the different modules to perform certain task is based on a Markov decision process (MDPs)
According to each task in this competition, the reward function of the MDP is defined, and by solving the MDP an optimal policy is obtained
Architecture:Modular, Layered, Distributed
Locali-zation
VoiceNaviga-
tionGestures Faces
Follow Me
Who’swho
Silhouettes Objects…
Lost & Found
…
Sensors Actuators
Shared Memory
PLUGIN’SLEVEL
EXECUTIONLEVEL
DECISIONLEVEL
Bye…