 For many years human being has been trying to recreate the complex mechanisms that human body forms & to copy or imitate human systems  As a result.

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Presentation transcript:

 For many years human being has been trying to recreate the complex mechanisms that human body forms & to copy or imitate human systems  As a result due to technical advancements humanoid robots came  Here,Presentation is about Machine Learning strategies for humanoid robots from social interactions

 Human caregivers often employ learning aids, such as books, educational videos, drawing boards, musical or textured toys, to teach a child.  Inspired in infant development, we developing a humanoid robot's perceptual system through the use of learning aids, cognitive artifacts, and educational activities  so that a robot learns about the world according to a child’s developmental phases

 Learning experiments are used for transmitting information to the humanoid robot Cog.  To learn about objects' multiple visual & auditory representations from books, musical instruments & educational activities such as drawing and painting  Our strategy relies heavily in human-robot interactions. For instance, it is essential to have a human in the loop to introduce objects from a book to the robot

 Aids uses to diverse a set of animate objects, exposing the latter to an outside world of colors, forms, shapes and contrasts.  Such as images of whales and cows  Since these learning aids help to expand the child's knowledge of the world, they are a potentially useful tool for introducing new informative percepts to a robot.

 Hand gestures trajectories are now applied to recover the geometric shape (set of lines computed by applying the Hough Transform)  Appearance( given by an image template enclosing such lines) of a scene object (as seen by the robot).  Visual geometries in a scene (such as circles) are recognized as such from hand gestures having the same geometry (as is the case of circular gestures).

 Training data for object/face recognition is extracted by keeping objects and others faces in memory for a while, generating a collection of training samples consisting of multiple segmentations of objects and faces.  (left) on-line experiment on Cog (right) schematic organization. 1. Object segmentation 2. Face detection and segmentation 3. Multiple object tracking 4. Object Recognition 5. Face Recognition.

 Industrial robots are being used in many manufacturing plants all over the world  A broad variety of robots are available for special applications from different manufactures  Humanoid robots work together in a shared space with humans.  They are designed as universal helpers and should be able to learn new skills and to apply them to new, previously unknown tasks

 THANK YOU!!