A vision based robot navigation and human tracking for social robotics

In this paper, we introduce a new vision based method for robot navigation and human tracking. For robot navigation, we convert the captured image in a binary one, which after the partition is used as the input of the neural controller. The neural control system, which maps the visual information to motor commands, is evolved online using real robots. For human tracking, after face detection, the color of human's clothing is extracted. Then the robot starts tracking the human in the environment. The performance of proposed method is evaluated using the TateRob mobile robot. The experimental results and analysis are presented.

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