Markovito’s Team (INAOE, Puebla, Mexico). Team members.

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Presentation transcript:

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 scanners with particle filters, represented as a probabilistic grid Visual features (SIFT) are integrated to 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 Locali- zation Voice Naviga- tion Naviga- tion Gestures Faces Follow Me Follow Me Who’s who Who’s who Silhouettes Objects … … Lost & Found Lost & Found … Sensors Actuators Shared Memory

Bye…